2562 Data Scientist Jobs - Page 37

About Yubi Yubi, formerly known as CredAvenue, is redefining global debt markets by freeing the flow of finance between borrowers, lenders, and investors. We are the world's possibility platform for the discovery, investment, fulfillment, and collection of any debt solution. At Yubi, opportunities are plentiful, and we equip you with the tools to seize them. In March 2022, we became India's fastest fintech and most impactful startup to join the unicorn club with a Series B fundraising round of $137 million. In 2020, we began our journey with a vision of transforming and deepening the global institutional debt market through technology. Our two-sided debt marketplace helps institutional and HNI investors find the widest network of corporate borrowers and debt products on one side and helps corporates to discover investors and access debt capital efficiently on the other side. Switching between platforms is easy, which means investors can lend, invest, and trade bonds - all in one place. All of our platforms shake up the traditional debt ecosystem and offer new ways of digital finance. Yubi Credit Marketplace - With the largest selection of lenders on one platform, our credit marketplace helps enterprises partner with lenders of their choice for any capital requirements. Yubi Invest - Fixed income securities platform for wealth managers & financial advisors to channel client investments in fixed income Financial Services Platform - Designed for financial institutions to manage co-lending partnerships & asset-based securitization Spocto - Debt recovery & risk mitigation platform Accumn - Dedicated SaaS solutions platform powered by Decision-grade data, Analytics, Pattern Identifications, Early Warning Signals, and Predictions to Lenders, Investors, and Business Enterprises So far, we have onboarded over 17,000+ enterprises and 6200+ investors & lenders and have facilitated debt volumes of over INR 1,40,000 crore. Backed by marquee investors like Insight Partners, B Capital Group, Dragoneer, Sequoia Capital, LightSpeed, and Lightrock, we are the only-of-its-kind debt platform globally, revolutionizing the segment. At Yubi, People are at the core of the business and our most valuable assets. Yubi is constantly growing, with 1000+ like-minded individuals today who are changing the way people perceive debt. We are a fun bunch who are highly motivated and driven to create a purposeful impact. Come join the club to be a part of our epic growth story. About the job Job Title: Data Scientist 2 (LLM/GenAI) Location: Bangalore Experience: 2 - 4 years Employment Type: Full-time Job Summary: We seek a highly skilled Data Scientist (LLM) to join our AI and Machine Learning team. The ideal candidate will have a strong foundation in Machine Learning (ML), Deep Learning (DL), and Large Language Models (LLMs) , along with hands-on experience in building and deploying conversational AI/chatbots . The role requires expertise in LLM agent development frameworks such as LangChain, LlamaIndex, AutoGen, and LangGraph . You will work closely with cross-functional teams to drive the development and enhancement of AI-powered applications. Key Responsibilities: Develop, fine-tune, and deploy Large Language Models (LLMs) for various applications, including chatbots, virtual assistants, and enterprise AI solutions. Build and optimize conversational AI solutions with at least 1 year of experience in chatbot development. Implement and experiment with LLM agent development frameworks such as LangChain, LlamaIndex, AutoGen, and LangGraph . Design and develop ML/DL-based models to enhance natural language understanding capabilities. Work on retrieval-augmented generation (RAG) and vector databases (e.g., FAISS, Pinecone, Weaviate, ChromaDB) to enhance LLM-based applications. Optimize and fine-tune transformer-based models such as GPT, LLaMA, Falcon, Mistral, Claude, etc., for domain-specific tasks. Develop and implement prompt engineering techniques and fine-tuning strategies to improve LLM performance. Work on AI agents, multi-agent systems, and tool-use optimization for real-world business applications. Develop APIs and pipelines to integrate LLMs into enterprise applications. Research and stay up-to-date with the latest advancements in LLM architectures, frameworks, and AI trends . Required Skills & Qualifications: 2-4 years of experience in Machine Learning (ML), Deep Learning (DL), and NLP-based model development. Hands-on experience in developing and deploying conversational AI/chatbots is Plus Strong proficiency in Python and experience with ML/DL frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers . Experience with LLM agent development frameworks like LangChain, LlamaIndex, AutoGen, LangGraph . Knowledge of vector databases (e.g., FAISS, Pinecone, Weaviate, ChromaDB) and embedding models . Understanding of Prompt Engineering and Fine-tuning LLMs . Familiarity with cloud services (AWS, GCP, Azure) for deploying LLMs at scale. Experience in working with APIs, Docker, FastAPI for model deployment. Strong analytical and problem-solving skills. Ability to work independently and collaboratively in a fast-paced environment. Good to Have: Experience with Multi-modal AI models (text-to-image, text-to-video, speech synthesis, etc.) . Knowledge of Knowledge Graphs and Symbolic AI . Understanding of MLOps and LLMOps for deploying scalable AI solutions. Experience in automated evaluation of LLMs and bias mitigation techniques . Research experience or published work in LLMs, NLP, or Generative AI is a plus. Why Join Us? This is an opportunity to work on cutting-edge LLM and Generative AI projects . Collaborative and innovative work environment. Competitive salary and benefits. Career growth opportunities in AI and ML research and development.

This role is for one of the Weekday's clients Salary range: Rs 2000000 - Rs 3000000 (ie INR 20-30 LPA) Min Experience: 3 years Location: Bengaluru JobType: full-time We are seeking a highly motivated and results-driven Data Scientist with 3 to 6 years of experience to join our growing data science team. In this role, you will work at the intersection of business and technology, transforming raw data into actionable insights and intelligent models that drive strategic decision-making. Your deep understanding of machine learning algorithms, strong command over Python, and proficiency in SQL will be critical to solving complex business problems and enabling data-driven innovation across the organization. Requirements Key Responsibilities: Develop, implement, and optimize machine learning models to solve real-world business problems such as customer segmentation, recommendation systems, predictive analytics, churn prediction, and more. Translate business requirements into analytical models and data products that align with company goals. Clean, preprocess, and manipulate large datasets from various structured and unstructured sources using Python and SQL. Build data pipelines and automate data workflows for scalable model deployment and monitoring. Collaborate closely with cross-functional teams including data engineering, product, marketing, and operations to define problem statements, prioritize tasks, and deliver solutions. Present findings, models, and recommendations to both technical and non-technical stakeholders through clear visualizations and storytelling. Continuously research and stay updated on the latest trends in machine learning, statistical modeling, and data science techniques to apply best practices and enhance model performance. Ensure the reliability, accuracy, and explainability of models, and participate in code reviews, model validation, and documentation. Skills and Qualifications: Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field. 3 to 6 years of hands-on experience in data science or machine learning roles. Strong proficiency in Python and its data science libraries (such as Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, TensorFlow or PyTorch). Solid experience with SQL for data querying, manipulation, and aggregation across large datasets. Demonstrated ability to build and deploy end-to-end machine learning models in production environments. Strong understanding of statistical analysis, data modeling, and algorithm design. Experience working with large-scale datasets, preferably in cloud environments (AWS, GCP, or Azure). Familiarity with tools like Jupyter Notebooks, Git, and CI/CD pipelines is a plus. Excellent problem-solving, critical thinking, and communication skills. Ability to work independently in a fast-paced, dynamic environment while collaborating effectively within a team

We are looking for qualified people who can develop scalable solutions to complex real-world problems using AI/ML, Big Data, Statistics, Econometrics, and Optimization. Potential candidates should have excellent depth and breadth of knowledge in machine learning, data mining, and statistical modeling. They should possess the ability to translate a business problem into an analytical problem, identify the relevant data sets needed for addressing the analytical problem, recommend, implement, and validate the best suited analytical algorithm(s), and generate/deliver insights to stakeholders. Candidates are expected to regularly refer to research papers and be at the cutting-edge with respect to algorithms, tools, and techniques. The role is that of an individual contributor; however, the candidate is expected to work in project teams of 2 to 3 people and interact with Business partners on regular basis. Minimum Qualifications Bachelor’s degree in Analytics, Computer science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. 2+ years of hands-on experience in Python programming for data analysis, machine learning, and with libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, NLTK, spaCy, and Gensim. 2+ years of experience with both supervised and unsupervised machine learning techniques. 2+ years of experience with data analysis and visualization using Python packages such as Pandas, NumPy, Matplotlib, Seaborn, or data visualization tools like Dash or PowerBI. 1+ years' experience in SQL programming language and relational databases. Preferred Qualifications An MS/PhD in Analytics, Computer Science, Operational research, Statistics, Applied mathematics or in any other engineering discipline. PhD strongly preferred. Experience working with Google Cloud Platform (GCP) services, leveraging its capabilities for ML model development and deployment. Experience with Git and GitHub for version control and collaboration. Besides Python, familiarity with one more additional programming language (e.g., C/C++/Java) Strong background and understanding of mathematical concepts relating to probabilistic models, conditional probability, numerical methods, linear algebra, neural network under the hood detail. Experience working with large language models such GPT-4, Gemini, Palm, Llama-2, etc. Excellent problem solving, communication, and data presentation skills Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making Design and implement data analysis and AI/ML models, hypotheses, algorithms and experiments to support data-driven decision-making Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness

🌟 Title: Data Scientist 📍 Location: Sector-48, Sohna Road, Gurgaon (Gurugram) - 122018 💼 Type: Hybrid – 3 days per week in Gurugram office 🚀 Start Date: Immediate (need someone who can join within 15 days or less) 💰 Compensation: 30-35 LPA (100% fixed) + benefits **Benefits include: 11 National Holidays and 15 PTO days Health Insurance: 30 Lakh for employee, spouse, two dependent children, and two parents/in-laws Accident & Disability: 50 Lakh for employee Free doctor consultations Key Requirements Must be able to work hybrid in Gurugram office 3 days per week Must be ready to join immediately within 15 days Must Haves: 5+ years of experience as a data scientist Statistics or mathematics background/degree Strong technical experience with Snowflake, Azure, Databricks, Python and SQL Plusses: Med device, healthcare, or pharmaceutical background Description: An employer is seeking an experienced Data Scientist based in Gurgaon, India to join an analytics organization for a global medical device client. This individual will support a major compliance initiative and serve as lead data scientist overseeing algorithm buildouts. They will be collaborating with the data engineering team to source and clean the data. They will also work closely with stakeholders to understand the specific requirements and will create algorithms based off of those specifications. The technology landscape includes: Databricks, Python, SQL, Snowflake and Azure.

Role As a Data Scientist, you will contribute to developing and deploying innovative AI and machine learning solutions that transform insurance operations through intelligent automation. You'll work on sophisticated models for Fraud, Waste & Abuse (FWA) detection, Intelligent Document Processing (IDP), and Agentic AI systems that power autonomous insurance workflows including underwriting, claims processing, and policy servicing. This role offers excellent opportunities for growth and learning - you'll contribute to core product development, support customer implementations, and assist with proof-of-concept development under the guidance of senior team members. Working with our advanced tech stack including LLM fine-tuning, computer vision, and multi-agent systems, you'll solve complex problems that directly impact how insurance companies operate and serve their customers. As we scale from successful startup to enterprise-level positioning, you'll develop your expertise in production machine learning, learn best practices from experienced practitioners, and contribute meaningfully to AI solutions that maintain the highest standards of accuracy, reliability, and business impact. If you're passionate about applying data science to real-world insurance challenges and want to grow your career while seeing your models transform business processes, this role offers excellent opportunities for professional development. Model Development & Implementation Develop and implement machine learning models for fraud detection, risk assessment, and anomaly detection using established algorithms and frameworks under senior guidance Build computer vision and NLP models for intelligent document processing, including document classification, OCR optimization, and automated information extraction Implement and fine-tune Large Language Models (LLMs) for insurance-specific applications, applying techniques such as LoRA, QLoRA, and PEFT to create domain-specialized solutions Develop predictive models for underwriting, claims processing, and medical risk assessment that support enhanced decision-making and operational efficiency Perform feature engineering and exploratory data analysis to identify patterns and insights that inform model development and business understanding AI Agent Development & Support Contribute to the development of autonomous AI agents for handling insurance workflows with appropriate supervision and guidance Implement agent components and workflows that support multi-agent coordination and decision-making processes Build conversational AI capabilities that can interact with users and systems to gather information and provide recommendations Support the development of intelligent decision-making systems that adapt to varying business requirements and regulatory constraints Assist with the implementation of agent monitoring, evaluation, and improvement processes Data Processing & Analysis Build and maintain data pipelines for model training, validation, and inference using modern data engineering tools and practices Implement data quality checks and validation processes that ensure model inputs meet accuracy and consistency requirements Perform comprehensive data analysis to understand data characteristics, identify quality issues, and inform model development decisions Create data visualizations and analytical reports that communicate insights to technical and business stakeholders Work with diverse data sources including structured insurance data, unstructured documents, and external data feeds Model Deployment & Monitoring Support Support model deployment processes from development through production, working with MLOps teams to ensure smooth transitions Implement model monitoring and performance tracking capabilities that detect issues and support continuous improvement Contribute to A/B testing and model evaluation frameworks that enable data-driven decisions about model performance Develop model documentation and explainability features that support business understanding and regulatory compliance Participate in model maintenance and improvement activities based on production performance and business feedback Collaboration & Learning Work closely with senior data scientists, solution architects, and software engineers to deliver high-quality technical solutions Support customer-facing activities by adapting models for specific client needs and contributing to implementation success Contribute to proof-of-concept development and technical demonstrations that Showcase Our Capabilities To Prospective Customers Participate in code reviews, technical discussions, and knowledge sharing activities that support team learning and best practices Stay current with emerging trends and techniques in AI/ML, particularly in areas relevant to insurance and autonomous agents Qualifications & Experience Academic Qualifications Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related quantitative field from a recognized institution Coursework or training in machine learning, statistics, or data analysis preferred Professional Experience 3+ years of hands-on experience in data science, machine learning, or related analytical roles with demonstrated ability to develop and deploy ML models Experience with machine learning project lifecycle from data exploration through model deployment Background in applying statistical methods and machine learning algorithms to solve business problems Exposure to production ML systems, model deployment, or MLOps practices Preferred Insurance industry exposure preferred, with understanding of claims processing, underwriting, medical risk assessment, or fraud detection workflows Technical Skills Strong proficiency in Python with experience using Scikit-Learn, Pandas, NumPy, and Jupyter for data science workflows Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar libraries for model development Basic to intermediate knowledge of LLM fine-tuning, natural language processing, or computer vision techniques. Understanding of embeddings, TF-IDF, and linguistic modelling. Familiarity with OCR technologies, document processing, or computer vision libraries such as OpenCV Experience with GenAI frameworks including LangChain, Hugging Face Transformers, or vector databases Knowledge of data manipulation and analysis using SQL, big data tools, or distributed computing frameworks Understanding of MLOps concepts, version control systems, and basic cloud platform usage Communication & Collaboration Skills Strong analytical and problem-solving skills with ability to approach complex business problems systematically Good communication abilities for presenting technical findings to team members and stakeholders Collaborative mindset with willingness to learn from senior team members and contribute to team success Attention to detail and commitment to producing high-quality, reliable analytical work Enthusiasm for learning new technologies and staying current with developments in AI/ML and insurance technology How We Get Things Done At our core, we believe in building intelligent systems that transform how insurance works. We're a team of innovators who combine deep technical expertise with real-world business impact. Our guiding principles center around technical excellence, data-driven decision making, and the responsible development of AI systems that enhance human capabilities. We foster a culture of continuous learning, experimentation, and cross-functional collaboration. As we scale from startup to enterprise, we maintain our commitment to cutting-edge research while building solutions that can handle the most demanding insurance workflows globally. Championing Inclusion & Innovation We embrace the opportunity to build a team that reflects diverse perspectives and experiences. Being an equal opportunity employer means we consider qualified candidates based on merit, technical capabilities, and cultural fit, regardless of background, identity, or personal characteristics. We're committed to creating an inclusive environment where innovative thinking thrives and where every team member can contribute to our mission of transforming insurance through intelligent automation. Skills: ml,processing,python,sql,pandas,pytorch,insurance,numpy,ocr technologies,data,machine learning,data science,learning,genai frameworks,scikit-learn,tensorflow,computer vision,data analysis,natural language processing,mlops,jupyter

Role As a Data Scientist, you will contribute to developing and deploying innovative AI and machine learning solutions that transform insurance operations through intelligent automation. You'll work on sophisticated models for Fraud, Waste & Abuse (FWA) detection, Intelligent Document Processing (IDP), and Agentic AI systems that power autonomous insurance workflows including underwriting, claims processing, and policy servicing. This role offers excellent opportunities for growth and learning - you'll contribute to core product development, support customer implementations, and assist with proof-of-concept development under the guidance of senior team members. Working with our advanced tech stack including LLM fine-tuning, computer vision, and multi-agent systems, you'll solve complex problems that directly impact how insurance companies operate and serve their customers. As we scale from successful startup to enterprise-level positioning, you'll develop your expertise in production machine learning, learn best practices from experienced practitioners, and contribute meaningfully to AI solutions that maintain the highest standards of accuracy, reliability, and business impact. If you're passionate about applying data science to real-world insurance challenges and want to grow your career while seeing your models transform business processes, this role offers excellent opportunities for professional development. Model Development & Implementation Develop and implement machine learning models for fraud detection, risk assessment, and anomaly detection using established algorithms and frameworks under senior guidance Build computer vision and NLP models for intelligent document processing, including document classification, OCR optimization, and automated information extraction Implement and fine-tune Large Language Models (LLMs) for insurance-specific applications, applying techniques such as LoRA, QLoRA, and PEFT to create domain-specialized solutions Develop predictive models for underwriting, claims processing, and medical risk assessment that support enhanced decision-making and operational efficiency Perform feature engineering and exploratory data analysis to identify patterns and insights that inform model development and business understanding AI Agent Development & Support Contribute to the development of autonomous AI agents for handling insurance workflows with appropriate supervision and guidance Implement agent components and workflows that support multi-agent coordination and decision-making processes Build conversational AI capabilities that can interact with users and systems to gather information and provide recommendations Support the development of intelligent decision-making systems that adapt to varying business requirements and regulatory constraints Assist with the implementation of agent monitoring, evaluation, and improvement processes Data Processing & Analysis Build and maintain data pipelines for model training, validation, and inference using modern data engineering tools and practices Implement data quality checks and validation processes that ensure model inputs meet accuracy and consistency requirements Perform comprehensive data analysis to understand data characteristics, identify quality issues, and inform model development decisions Create data visualizations and analytical reports that communicate insights to technical and business stakeholders Work with diverse data sources including structured insurance data, unstructured documents, and external data feeds Model Deployment & Monitoring Support Support model deployment processes from development through production, working with MLOps teams to ensure smooth transitions Implement model monitoring and performance tracking capabilities that detect issues and support continuous improvement Contribute to A/B testing and model evaluation frameworks that enable data-driven decisions about model performance Develop model documentation and explainability features that support business understanding and regulatory compliance Participate in model maintenance and improvement activities based on production performance and business feedback Collaboration & Learning Work closely with senior data scientists, solution architects, and software engineers to deliver high-quality technical solutions Support customer-facing activities by adapting models for specific client needs and contributing to implementation success Contribute to proof-of-concept development and technical demonstrations that Showcase Our Capabilities To Prospective Customers Participate in code reviews, technical discussions, and knowledge sharing activities that support team learning and best practices Stay current with emerging trends and techniques in AI/ML, particularly in areas relevant to insurance and autonomous agents Qualifications & Experience Academic Qualifications Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or related quantitative field from a recognized institution Coursework or training in machine learning, statistics, or data analysis preferred Professional Experience 3+ years of hands-on experience in data science, machine learning, or related analytical roles with demonstrated ability to develop and deploy ML models Experience with machine learning project lifecycle from data exploration through model deployment Background in applying statistical methods and machine learning algorithms to solve business problems Exposure to production ML systems, model deployment, or MLOps practices Preferred Insurance industry exposure preferred, with understanding of claims processing, underwriting, medical risk assessment, or fraud detection workflows Technical Skills Strong proficiency in Python with experience using Scikit-Learn, Pandas, NumPy, and Jupyter for data science workflows Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar libraries for model development Basic to intermediate knowledge of LLM fine-tuning, natural language processing, or computer vision techniques. Understanding of embeddings, TF-IDF, and linguistic modelling. Familiarity with OCR technologies, document processing, or computer vision libraries such as OpenCV Experience with GenAI frameworks including LangChain, Hugging Face Transformers, or vector databases Knowledge of data manipulation and analysis using SQL, big data tools, or distributed computing frameworks Understanding of MLOps concepts, version control systems, and basic cloud platform usage Communication & Collaboration Skills Strong analytical and problem-solving skills with ability to approach complex business problems systematically Good communication abilities for presenting technical findings to team members and stakeholders Collaborative mindset with willingness to learn from senior team members and contribute to team success Attention to detail and commitment to producing high-quality, reliable analytical work Enthusiasm for learning new technologies and staying current with developments in AI/ML and insurance technology How We Get Things Done At our core, we believe in building intelligent systems that transform how insurance works. We're a team of innovators who combine deep technical expertise with real-world business impact. Our guiding principles center around technical excellence, data-driven decision making, and the responsible development of AI systems that enhance human capabilities. We foster a culture of continuous learning, experimentation, and cross-functional collaboration. As we scale from startup to enterprise, we maintain our commitment to cutting-edge research while building solutions that can handle the most demanding insurance workflows globally. Championing Inclusion & Innovation We embrace the opportunity to build a team that reflects diverse perspectives and experiences. Being an equal opportunity employer means we consider qualified candidates based on merit, technical capabilities, and cultural fit, regardless of background, identity, or personal characteristics. We're committed to creating an inclusive environment where innovative thinking thrives and where every team member can contribute to our mission of transforming insurance through intelligent automation. Skills: ml,processing,python,sql,pandas,pytorch,insurance,numpy,ocr technologies,data,machine learning,data science,learning,genai frameworks,scikit-learn,tensorflow,computer vision,data analysis,natural language processing,mlops,jupyter

AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do You Dream Big? We Need You. Job Description Job Title: Data Scientist Location: Bangalore Reporting to: Senior Manager Analytics 1) Purpose of the role Anheuser-Busch InBev (AB InBev)ʼs Logistics Analytics team is responsible for transforming the company’s Supply Chain by embedding intelligence across key process areas in Inventory Planning, Transportation & Warehousing. 2) Key tasks & accountabilities Collaborate with product owners from business functions to translate business problem into Data Science use case. Expected to explore and develop ML/AI algorithms to solve new business problem or improve the existing methodology, model accuracy etc. Work on building code that will deploy into production, using code design and style standards. Document your thought process and create artefacts on team repo/wiki that can be used to share with business and engineering for sign-off. Significantly improve the performance and reliability of our code that create high quality and reproducible results. Collaborate with other team members to advance teamʼs ability to ship high quality code, fast! Maintain basic developer hygiene that includes but not limited to, writing tests, using loggers, readme to name a few. 3) Qualifications, Experience, Skills Level of educational attainment required Academic degree in, but not limited to, Bachelors or Masters in engineering (CS) B.Tech/BE/ Masters in data science, statistics, applied mathematics, mathematics, economics, etc Previous work experience Minimum 3- 6+ years of relevant experience in Analytics & Data science / building ML models Preferred industry exposure – CPG or Supply Chain domain & capability of successfully deploying analytics solutions and products for internal or external clients Technical Skills required Hands-on experience in data manipulation using Excel, Python, SQL Expert level proficiency in Python (knowledge of object-oriented design concepts & able to write end-to-end ML or data pipelines in python) Proficient in application of one or more and has exposure to others - ML concepts (like regression, classification, clustering, time series forecasting) and optimization techniques(Linear & Non Linear optimization) to solve end-to-end business problem. Familiarity with Azure Tech Stack, Databricks, ML Flow in any cloud platform Other Skills required Passion for solving problems using data Detail oriented, analytical and inquisitive. Ability to learn on the go Ability to effectively communicate and present information at various levels of an organization Ability to work independently and with others And above all of this, an undying love for beer! We dream big to create future with more cheers!

Experience in Programming (Python, R, SQL, NoSQL, Spark) with ML tools & Cloud Technology (AWS, Azure, GCP) Experience in Python libraries such as NumPy, pandas, scikit-learn, tensor-flow, scapy, scrapy, BERT etc. Good understanding in statistics, and ability to design statistical hypothesis testing to aid formal decision making. Develops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, linear regression, PCA etc.) Engaging with clients, understanding complex problem statements, and offering solutions in the domains of Retail, Pharma, Banking, Insurance, etc. Contribute to internal product development initiatives related to data science. Develop data science roadmap, and guide data scientist to meet their deliverables. Handling end-to-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and client interaction. Proven ability to discover solutions hidden in large datasets and to drive business results with their data-based insights Drive excellent project management required to deliver complex projects, including effort/time estimation. Be proactive, with full ownership of the engagement. Build scalable client engagement level processes for faster turnaround & higher accuracy Define Technology/ Strategy and Roadmap for client accounts, and guides implementation of that strategy within projects Run regular project reviews and audits to ensure that projects are being executed within the guardrails agreed by all stakeholders Manage the team-members, to ensure that the project plan is being adhered to over the course of the project Manage the client stakeholders, and their expectations, with a regular cadence of weekly meetings and status updates. Build a trusted advisor relationship with the IT management at clients and internal accounts leadership. Build business case for technological investments to be made for future needs and to remain competitive Ensure that billing and utilization of team members is maximized throughout the year

Skills : Python AI/ML & ML Ops Practices Machine Learning and deep Learning Cloud - GCP/AWS/Azure AI/Ml,NLP,LLM DevOps - Docker, Kubernetes, and Git Frontend development and API integration We are seeking a talented and experienced AI Engineer to join our dynamic team. Theideal candidate will have a strong background in Python programming, with extensiveexperience in API development, microservices, and working with both SQL and NoSQLdatabases. Familiarity with Python frameworks such as Flask and FastAPI is essential. Thisrole involves developing high-quality, scalable, and robust applications and services,contributing to a range of projects that make a real impact. Key Responsibilities: Design, build, and maintain efficient, reusable, and reliable Python code. Develop and maintain RESTful APIs and services. Work with SQL and NoSQL databases to store and manipulate data effectively. Build scalable microservices and integrate them into larger application ecosystems. Collaborate with cross-functional teams to understand user requirements andprovide technical solutions. Contribute to all phases of the development lifecycle, from concept to deploymentand maintenance. Troubleshoot, test, and maintain the core product software to ensure strongoptimization and functionality. Keep up-to-date with the latest industry trends and technologies in Pythondevelopment.

Overview: An expert in their field, applying broad business knowledge and strategic insight surrounding emerging trends and technologies to solve complex problems and drive organizational results. Leads critical, high-impact projects and designs/implements innovative business strategies. Works with minimal oversight, frequently consulting senior leadership and influencing executive decisions. Serves as a mentor and assists others with challenging issues. Performs very complex data science work, creates new ways of analyzing data, builds very complex business models, and makes recommendations that impact an entire business unit or very large complex sector. Key Roles and Responsibilities: Typical tasks may include, but are not limited to, the following: Data Extraction and Preparation: Collect data from various structured and unstructured sources (datalakes, databases, data warehouses, on cloud, internal, external) and ensure its quality for analysis through cleaning and preprocessing. Designs, builds, and analyzes large (e.g. 100 s of Terabytes or higher as technology advances) and complex data sets while thinking strategically about data use and data design. Tools can include snowflake and databricks. Coding Solutions, Algorithms and Feature Engineering: Create relevant features and conduct exploratory data analysis. Codes solutions following typical workflow; data extraction, cleansing, feature engineering, exploratory data analysis, model selection/creation, hyper-parameter tuning, model interpretation, model retraining, business process and/or system implementations, high level proof of concept and trials, visualization, deployment to production, post deployment ML ops monitoring / diagnosis / resolutions. Coding proficiency required in at least one data science language (Python, R, Scala, etc.), as well as expertise with modern ML packages and libraries (Spark, SciKitLearn, Pandas, PyTorch, TidyVerse, Tensorflow, Keras, Shiny, and/or AutoML tools). Model Development, Deployment and Optimization: Build, evaluate, and optimize machine learning models through hyperparameter tuning. Implement models into production, continuously monitor their performance, and ensure they remain explainable and reliable to minimize model decay. Ability to develop custom Machine Learning (ML). Highly proficient in the full AI workflow such as (1) data extraction, cleansing, feature engineering, exploratory data analysis, model selection/creation, hyper-parameter tuning, model interpretation, model retraining and (2) Uses concepts like mlflow to log metrics. Well-versed in Interactive Development Environments (IDEs) such as Databricks Workspaces or Visual Studio Code. Proficiency in algorithm categories such as Supervised Learning, Unsupervised Learning, Optimization Algorithms, Deep Learning, AI-Computer Vision, Natural Language Processing, Deep Reinforcement Learning, Search Algorithms, and AI- Knowledge Graphs. Visualization and Collaboration: Create visualizations and reports for stakeholders while working closely with cross-functional teams to align efforts with business objectives. Can utilize advanced coding methods to produce visualizations (e.g. ggplot, D3.js, etc.). Generative AI: Develop and implement generative AI models, focusing on creating new content or augmenting existing data. Generative Models-Understanding of GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and Transformers. Fine-Tuning-Techniques for adapting pre-trained models to specific tasks using smaller, task-specific datasets. Agentics-Understanding of agentic architecture, concepts and optimization of solutions. Prompt Engineering-Crafting effective prompts to guide generative models in producing desired outputs. Retrieval-Augmented Generation (RAG)-Combining generative models with retrieval systems to enhance performance and relevance. Text Generation-Proficiency in using models like GPT-3/4 for generating human-like text. Image Generation-Familiarity with tools like DALL-E and Stable Diffusion for creating images from text descriptions. Key Skills: Python, R, Scala, Generative AL, Credit, Modele development, Fraud, tiral analysis, Machine Learning (ML), Snowflake, databricks, Spark, SciKitLearn, Pandas, PyTorch, TidyVerse, Tensorflow, Keras, Shiny, AutoML Job ID R-72967 Date posted 06/30/2025

Job Description: Data Scientist (Generative AI) Job Summary Astria Digital is hiring a skilled and innovative AI/ML Engineer for an exciting Conversational AI Bot project. This role is available in a hybrid setup (Bangalore) or can be fully remote. We re seeking someone with deep knowledge of AI/ML fundamentals, strong hands-on experience with modern NLP tech stacks, and the ability to build and deploy Small Language Models (SLMs). You ll work on creating intelligent, responsive conversational systems using frameworks like Lang Chain and deploying models on cloud platforms such as AWS or Azure. If youre passionate about cutting-edge language models and building real-world AI solutions, we d love to connect. Skills & Responsibilities Design, develop, and optimize Conversational AI Bots using advanced NLP techniques Build and fine-tune Small Language Models (SLMs) and integrate them into conversational flows Use frameworks like LangChain, LlamaIndex, or similar to develop memory-aware, context-rich dialogue systems Implement Retrieval-Augmented Generation (RAG) and embedding techniques for intelligent responses Deploy custom-trained models on AWS (e.g., SageMaker, Lambda) or Azure (e.g., AKS, ML Studio) Deep understanding of LLM architecture, transformers, and prompt engineering Proficient with libraries such as Hugging Face Transformers, PyTorch, TensorFlow Familiarity with vector databases (e.g., FAISS, Pinecone) and chat memory stores Strong foundation in machine learning fundamentals, optimization, and evaluation techniques Collaborate with product and engineering teams to integrate AI into scalable applications Experience with MLOps, model monitoring, and continuous improvement of conversational performance Keep up with the latest advancements in Conversational AI, open-source LLMs, and fine-tuning method

Silicon Labs (NASDAQ: SLAB) is the leading innovator in low-power wireless connectivity, building embedded technology that connects devices and improves lives. Merging cutting-edge technology into the world s most highly integrated SoCs, Silicon Labs provides device makers the solutions, support, and ecosystems needed to create advanced edge connectivity applications. Headquartered in Austin, Texas, Silicon Labs has operations in over 16 countries and is the trusted partner for innovative solutions in the smart home, industrial IoT, and smart cities markets. Learn more at www.silabs.com . What Youll do Lead and execute complex data science initiatives that support high-impact business decisions. Responsible for the development, deployment, and communication of advanced analytical models. Provides technical guidance to junior data scientists and partners closely with cross-functional teams to drive data-driven outcomes Responsibilities Designs and implements advanced statistical and machine learning models to solve complex business problems. Leads full-cycle analytics projects, including problem definition, data exploration, model development, evaluation, and deployment. Collaborates with stakeholders to align data science solutions with business goals and priorities. Provides technical mentorship to junior team members and contributes to knowledge sharing across the team. Translates complex modeling outputs into actionable insights and presents findings to senior leadership. Stays current on industry best practices and emerging trends in AI, machine learning, and data science tools. Contributes to continuous improvement in analytical workflows, code standards, and data governance. Applies sound judgment to navigate ambiguous problems and propose scalable solutions. Performs other duties as required in support of the data science team and organizational goals. Required Qualification and skills Bachelor s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field; Master s preferred. Minimum of 4 years of experience in data science, machine learning, or advanced analytics. Advanced proficiency in Python or R, SQL, and machine learning libraries (e.g., scikit-learn, TensorFlow). Strong grasp of statistical analysis, experimental design, and model evaluation techniques. Excellent written and verbal communication skills, with the ability to influence both technical and non-technical stakeholders. Demonstrated experience in leading complex data projects and driving measurable business outcomes. Experience with cloud-based data platforms (e.g., AWS, GCP, Azure) and MLOps practices is a plus. Benefits & Perks: Not only will you be joining a highly skilled and tight-knit team where every engineer makes a significant impact on the product; we also strive for good work/life balance and to make our environment welcoming and fun. Equity Rewards (RSUs) Employee Stock Purchase Plan (ESPP) Insurance plans with Outpatient cover National Pension Scheme (NPS) Flexible work policy Childcare support Silicon Labs is an equal opportunity employer and values the diversity of our employees. Employment decisions are made on the basis of qualifications and job-related criteria without regard to race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status, or any other characteristic protected by applicable law.

Role Summary: Aurigo is leading the charge in transforming enterprise SaaS for infrastructure, and AI is at the core of this revolution. With Aurigo Lumina, our AI copilot, we are redefining how infrastructure owners interact with Masterworks, driving smarter, faster, and more efficient decision-making. We have set up AI Labs to build AI-powered software and transform Aurigo into an AI-first company. We have AI initiatives across the products and platforms. We are seeking an experienced Senior / Staff Data Scientist to build and deploy our AI/ML, Gen AI and agentic AI products and solutions. Key Responsibilities This position offers an opportunity to be part of the AI transformation of our organization, working with cutting-edge technologies and solving complex challenges in a collaborative environment. We are seeking a highly skilled Senior / Staff Data Scientist to carry out design, and scalable implementation of AI/Gen AI products and platforms. This role demands an individual with strong programming and debugging skills, good software development experience, deep expertise in cutting-edge AI models, architectures, and a strong commitment to responsible AI practices. Qualifications: Bachelor s or Master s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field 3+ years of progressive experience in AI/ML, Gen AI 3+ years of software development experience and strong coding skills Building predictive and prescriptive AI/ML models and domain-specific AI models for full construction lifecycle Strong expertise with LLMs (e.g., GPT, Claude, Mistral) Experience in Prompt engineering, RAG, Parameter Efficient Fine Tuning (PEFT), Reinfocement Learning with Human Feedback (RLHF) to improve the LLM responses including guardrails, evaluation and LLM observability to reduce hallucinations. Expertise in Natural Language Processing, transformers and knowledge graphs Proficiency in cloud platforms for AI architecture: AWS Bedrock, AWS SageMaker with a deep understanding of their AI service offerings. Experience of building autonomous/agentic AI systems (e.g., multi-agent frameworks, self-optimizing systems, or LLM-driven decision engines). Extensive hands-on experience with autonomous AI tools and frameworks: LangChain, Autogen, CrewAI, or architecting custom agentic frameworks. Expertise with Python, TensorFlow, PyTorch, or other relevant AI/ML libraries. Push proofs of concept to production-grade systems handling performance metrics, latency, and scale. About Aurigo Aurigo is revolutionizing how the world plans, builds, and manages infrastructure projects with Masterworks , our industry-leading enterprise SaaS platform. Trusted by over 300 customers managing $300 billion in capital programs, Masterworks is setting new standards for project delivery and asset management. Recognized as one of the Top 25 AI Companies of 2024 and a Great Place to Work for three consecutive years, we are leveraging artificial intelligence to create a smarter, more connected future for customers in transportation, water and utilities, healthcare, higher education, and the government, with over 40,000 projects across North America. At Aurigo, we don t just develop software we shape the future. If you re excited to join a fast-growing company and collaborate with some of the brightest minds in the industry to solve real-world challenges, let s connect. Competencies

Min 1-3 yrs of exp in data science,NLP&Python Exp in PyTorch,Scikit-learn,and NLP libraries(NLTK,SpaCy,Hugging Face) Help deploy AI/ML solutions on AWS,GCP/Azure Exp in SQL for data manipulation & analysis Exp in Big Data processing Spark,Pandas,Dask

Location : Hyderabad Role Highlights: As a Manager - Data Science , you wont just manage, youll lead by doing . This role demands strong hands-on expertise in Machine Learning, Generative AI, Python, and SQL , and any cloud environment (GCP, Azure or AWS) ensuring that you stay deeply engaged in the technical side while mentoring and growing a high-performing team. Youll spearhead end-to-end AI/ML project execution , collaborate with cross-functional teams, and drive innovation within Blends Data Science practice. If you love solving complex problems, thrive in a fast-paced environment, and can translate business challenges into cutting-edge AI solutions, wed love to have you on board! What Youll Tackle Each Day: Delivery & Project Management: Develop and implement ML models, Gen AI solutions, and predictive analytics . Perform data mining, feature engineering, and statistical analysis . Own project roadmaps, quality control, and timely delivery . Collaborate with Data Engineering teams to deploy and operationalize ML models . Automate and optimize workflows for efficiency. Practice Development: Contribute to scaling Blends Data Science practice by building new capabilities. Design industry-specific AI/ML solutions and contribute to thought leadership. Evaluate emerging AI trends and tools and integrate them into our ecosystem. Lead innovation initiatives , research, and internal AI development. People & Leadership: Mentor and develop a high-performance data science team . Guide career development and set performance benchmarks. Collaborate with cross-functional teams to drive seamless execution. 8+ years of experience in Data Science & AI , with hands-on expertise in ML, Python, and SQL . Exposure to Generative AI Should have worked on at least a few POCs or pilo

We are seeking a highly skilled Senior Data Scientist with experience in pricing optimization, pricing elasticity, and AWS SageMaker. The ideal candidate will have a strong foundation in Statistics and Machine Learning, with a particular focus on Bayesian modeling. As part of our Data Science team, you will work closely with clients to develop advanced pricing strategies using state-of-the-art tools and techniques, including AWS SageMaker, to optimize business outcomes. Key Responsibilities: Lead and contribute to the development of pricing optimization models, leveraging statistical and machine learning techniques to inform strategic decisions. Analyze pricing elasticity to predict consumer response to changes in price, helping clients maximize revenue and market share. Implement and deploy machine learning models using AWS SageMaker for scalable and efficient performance in a cloud environment. Utilize Bayesian modeling to support decision-making processes, providing insights into uncertainty and model predictions. Collaborate with cross-functional teams to integrate data-driven insights into business processes. Communicate complex results and findings in a clear and concise manner to both technical and non-technical stakeholders. Continuously explore and experiment with new modeling approaches and tools to improve accuracy and efficiency of pricing solutions. Bachelor s or Master s degree in Data Science, Statistics Mathematics Economics, or a related field. Advanced degrees preferred. 5+ years of hands-on experience in data science, with a focus on pricing optimization and elasticity mode

We are seeking a highly skilled Lead Data Scientist with experience in pricing optimization, pricing elasticity, and AWS SageMaker. The ideal candidate will have a strong foundation in Statistics and Machine Learning, with a particular focus on Bayesian modeling. As part of our Data Science team, you will work closely with clients to develop advanced pricing strategies using state-of-the-art tools and techniques, including AWS SageMaker, to optimize business outcomes. Key Responsibilities: Lead and contribute to the development of pricing optimization models, leveraging statistical and machine learning techniques to inform strategic decisions. Analyze pricing elasticity to predict consumer response to changes in price, helping clients maximize revenue and market share. Implement and deploy machine learning models using AWS SageMaker for scalable and efficient performance in a cloud environment. Utilize Bayesian modeling to support decision-making processes, providing insights into uncertainty and model predictions. Collaborate with cross-functional teams to integrate data-driven insights into business processes. Communicate complex results and findings in a clear and concise manner to both technical and non-technical stakeholders. Continuously explore and experiment with new modeling approaches and tools to improve accuracy and efficiency of pricing solutions. Bachelor s or Master s degree in Data Science, Statistics Mathematics Economics, or a related field. Advanced degrees preferred. 7+ years of hands-on experience in data science, with a focus on pricing optimization and elasticity mode

">Data Science 6-10 Years Bengaluru Data science Job Summary: We are looking for an experienced and innovative Senior Data Scientist with 6 to 10 years of experience, specializing in Generative AI (GenAI) , Large Language Models (LLMs) , and Natural Language Processing (NLP) . The ideal candidate will have deep expertise in developing and deploying AI/ML solutions, including Retrieval-Augmented Generation (RAG) frameworks, and working with cloud platforms such as Google Cloud Platform (GCP) . Key Responsibilities: Design, develop, and deploy advanced AI/ML models with a focus on NLP, GenAI, and LLMs. Implement and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise applications. Collaborate with cross-functional teams to translate business problems into AI solutions. Evaluate and fine-tune foundation models (e.g., GPT, PaLM, LLaMA) for domain-specific use cases. Work with cloud services (primarily GCP) for scalable model training and deployment. Develop robust data pipelines and conduct data preprocessing and feature engineering. Stay current with the latest advancements in GenAI, deep learning, and NLP. Mentor junior data scientists and contribute to knowledge sharing and best practices. Required Skills and Qualifications: Bachelor s or Master s degree in Computer Science, Data Science, AI/ML, or a related field. A PhD is a plus. 6 to 10 years of hands-on experience in data science or machine learning roles. Strong programming skills in Python ; familiarity with R is a plus. Proven experience with Generative AI , LLMs , and NLP frameworks (e.g., Hugging Face Transformers, SpaCy, NLTK). Practical knowledge of RAG architectures and vector databases (e.g., FAISS, Pinecone). Solid experience in deep learning using libraries such as TensorFlow, PyTorch, or JAX. Hands-on experience with Google Cloud Platform (GCP) services such as Vertex AI, BigQuery, and Cloud Storage. Excellent problem-solving skills and the ability to work independently or within a team. Preferred Qualifications: Experience in deploying LLMs in production environments. Knowledge of prompt engineering and fine-tuning techniques. Familiarity with CI/CD workflows for machine learning. Background in MLOps and model monitoring in cloud environments.

JD Primary skills: • Solid experience in building ML Models. • Proficient in SQL, Python, PySpark, Spark ML language. • Good understanding of cloud platforms such as AWS (preferred), Azure or GCP. • Proficient in source code controls using Github. Secondary skills: • Experience using any Auto ML products like DataRobot / H2O AI. • Provide inputs to build Artificial Intelligence (AI) roadmap for marketing based on TE&O architecture and capability delivery timelines. • Accountable for identifying, embedding, promoting, and ensuring continuous improvement within the use of new data and advanced analytics across the teams

Mirafra Technologies is Hiring #GenAIEngineer (#RAG, #LLM, #FineTuning) Are you passionate about Generative AI and cutting-edge technologies? Join We're looking for Gen AI Engineers with 3 to 5 years of experience in: Walk-In Date: Thursday, 3rd July 2025 Time: 11:00 AM 1:00 PM Job Location - #Bangalore and #Hyderabad Venue: Mirafra Technologies 2nd Floor, Akshay Tech Park, Plot No. 72 & 73, Vijayanagar, EPIP Zone, Whitefield, Bengaluru, Karnataka 560066 Contact Person: Vignesh D Requirements: 3 to 5yrs Strong experience with Gen AI frameworks Hands-on with LLM architecture and deployment Familiarity with RAG pipelines and fine-tuning techniques Solid programming skills in Python

About the Role: Grade Level (for internal use): 11 The Team As a member of the EDO, Collection Platforms & AI Cognitive Engineering team you will work on building GenAI-driven and ML-powered products and capabilities to power natural language understanding, data extraction, information retrieval and data sourcing solutions for S&P Global. You will define AI strategy, mentor others, and drive production-ready AI products and pipelines while leading by example in a highly engaging work environment. You will work in a (truly) global team and be encouraged for thoughtful risk-taking and self-initiative. Whats in it for you: Be a part of a global company and build solutions at enterprise scale Lead and grow a highly skilled, hands-on technical team (including mentoring junior data scientists) Contribute to solving high-complexity, high-impact problems end-to-end Architect and oversee production-ready pipelines from ideation to deployment Responsibilities: Define AI roadmap, tooling choices, and best practices for model building, prompt engineering, fine-tuning, and vector retrieval systems Architect, develop and deploy large-scale ML and GenAI-powered products and pipelines Own all stages of the data science project lifecycle, including: Identification and scoping of high-value data science and AI opportunities Partnering with business leaders, domain experts, and end-users to gather requirements and align on success metrics Evaluation, interpretation, and communication of results to executive stakeholders Lead exploratory data analysis, proof-of-concepts, model benchmarking, and validation experiments for both ML and GenAI approaches Establish and enforce coding standards, perform code reviews, and optimize data science workflows Drive deployment, monitoring, and scaling strategies for models in production (including both ML and GenAI services) Mentor and guide junior data scientists; foster a culture of continuous learning and innovation Manage stakeholders across functions to ensure alignment and timely delivery Technical : Hands-on experience with large language models (e.g., OpenAI, Anthropic, Llama), prompt engineering, fine-tuning/customization, and embedding-based retrieval Expert proficiency in Python (NumPy, Pandas, SpaCy, scikit-learn, PyTorch/TF 2, Hugging Face Transformers) Deep understanding of ML & Deep Learning models, including architectures for NLP (e.g., transformers), GNNs, and multimodal systems Strong grasp of statistics, probability, and the mathematics underpinning modern AI Ability to surf and synthesize current AI/ML research, with a track record of applying new methods in production Proven experience on at least one end-to-end GenAI or advanced NLP projectcustom NER, table extraction via LLMs, Q&A systems, summarization pipelines, OCR integrations, or GNN solutions Familiarity with orchestration and deployment toolsDocker, Airflow, Kubernetes, Redis, Flask/Django/FastAPI, PySpark, SQL, R-Shiny/Dash/Streamlit Openness to evaluate and adopt emerging technologies and programming languages as needed Good to have: Masters or Ph.D. in Computer Science, Statistics, Mathematics, or related field (minimum Bachelors) 6+ years of relevant experience in Data Science/AI, with at least 2 years in a leadership or technical lead role Prior experience in the Economics/Financial industry, especially with market-intelligence or risk analytics products Public contributions or demos on GitHub, Kaggle, StackOverflow, technical blogs, or publications Whats In It For You Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technologythe right combination can unlock possibility and change the world.Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you cantake care of business. We care about our people. Thats why we provide everything youand your careerneed to thrive at S&P Global. Health & WellnessHealth care coverage designed for the mind and body. Continuous LearningAccess a wealth of resources to grow your career and learn valuable new skills. Invest in Your FutureSecure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly PerksIts not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the BasicsFrom retail discounts to referral incentive awardssmall perks can make a big difference. For more information on benefits by country visithttps://spgbenefits.com/benefit-summaries Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected andengaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. Recruitment Fraud Alert If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to reportfraud@spglobal.com. S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, pre-employment training or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here. ----------------------------------------------------------- Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf ----------------------------------------------------------- 20 - Professional (EEO-2 Job Categories-United States of America), IFTECH202.2 - Middle Professional Tier II (EEO Job Group), SWP Priority Ratings - (Strategic Workforce Planning)

About the Role: Grade Level (for internal use): 10 The Team The Capital IQ Solutions Data Science team supports the S&P Capital IQ Pro platform with innovative Data Science and Machine Learning solutions, utilizing the most advanced NLP Generative AI models. This role presents a unique opportunity for hands-on ML/NLP/Gen AI/LLM scientists and engineers to advance to the next step in their career journey and apply their technical expertise in NLP, deep learning, Gen AI, and LLMs to drive business value for multiple stakeholders while conducting cutting-edge applied research in LLMs, Gen AI, and related areas. Responsibilities and Impact Design solutions utilizing NLP models including chat assistants and RAG systems. Design and develop custom NLP LLM Models including both prompt engineering techniques and model fine-tunning and alignment (SFT, RLHF, DPO) NLP Model evaluation using both human-supported and synthetic evaluation methods and metrics. Deploy NLP models ensuring latency, reliability, and scalability. Discover new methods for prompt engineering, model fine-tuning, quantization and latency optimization, document embeddings and chunking. Collaborate closely with product teams, business stakeholders, and engineers to ensure smooth integration of NLP models into production systems. Troubleshoot complex issues related to machine learning model development and data pipelines and develop innovative solutions. Actively research, explore and identify the latest relevant methods and technologies What Were Looking For : Basic Required Qualifications : Degree in Computer Science, Mathematics or Statistics, Computational linguistics, Engineering, or a related field. Good understanding ofmachine learning and deeplearningmethods and their mathematical foundations 5-8 years of professional experience in Advanced Analytics / Data Science / Machine Learning 5-8 years hands-on experience developing NLP models, ideally with transformer architectures. Demonstrated experience with Python, PyTorch, Hugging Face or similar tools. Mastery of Python and ability to write robust and high standard, testable code Knowledge of developing or tuning LLMS Additional Preferred Qualifications 3+ years of experience with implementing information retrieval systems. Experience with contributing to Open Source initiatives or in research projects and/or participation in Kaggle competitions. Publications related to Machine Learning or Deep Learning Ability to work in a team Able to report progress and summarize issues to a less technical audience Curious and open-minded attitude to new approaches About S&P Global Market Intelligence At S&P Global Market Intelligence, a division of S&P Global we understand the importance of accurate, deep and insightful information. Our team of experts delivers unrivaled insights and leading data and technology solutions, partnering with customers to expand their perspective, operate with confidence, andmake decisions with conviction.For more information, visit www.spglobal.com/marketintelligence . Whats In It For You Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technologythe right combination can unlock possibility and change the world.Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you cantake care of business. We care about our people. Thats why we provide everything youand your careerneed to thrive at S&P Global. Health & WellnessHealth care coverage designed for the mind and body. Continuous LearningAccess a wealth of resources to grow your career and learn valuable new skills. Invest in Your FutureSecure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly PerksIts not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the BasicsFrom retail discounts to referral incentive awardssmall perks can make a big difference. For more information on benefits by country visithttps://spgbenefits.com/benefit-summaries Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected andengaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. Recruitment Fraud Alert If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to reportfraud@spglobal.com. S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, pre-employment training or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity here. ----------------------------------------------------------- Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf ----------------------------------------------------------- , SWP Priority Ratings - (Strategic Workforce Planning)

Huebits is looking for Data science and Engineering Intern to join our dynamic team and embark on a rewarding career journey Undertaking data collection, preprocessing and analysis Building models to address business problems Presenting information using data visualization techniques Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams

Job Description We are seeking a highly skilled Senior Data Scientist with experience in pricing optimization, pricing elasticity, and AWS SageMaker. The ideal candidate will have a strong foundation in Statistics and Machine Learning, with a particular focus on Bayesian modeling. As part of our Data Science team, you will work closely with clients to develop advanced pricing strategies using state-of-the-art tools and techniques, including AWS SageMaker, to optimize business outcomes. Key Responsibilities: Lead and contribute to the development of pricing optimization models, leveraging statistical and machine learning techniques to inform strategic decisions. Analyze pricing elasticity to predict consumer response to changes in price, helping clients maximize revenue and market share. Implement and deploy machine learning models using AWS SageMaker for scalable and efficient performance in a cloud environment. Utilize Bayesian modeling to support decision-making processes, providing insights into uncertainty and model predictions. Collaborate with cross-functional teams to integrate data-driven insights into business processes. Communicate complex results and findings in a clear and concise manner to both technical and non-technical stakeholders. Continuously explore and experiment with new modeling approaches and tools to improve accuracy and efficiency of pricing solutions. Qualifications Bachelor s or Master s degree in Data Science, Statistics Mathematics Economics, or a related field. Advanced degrees preferred. 5+ years of hands-on experience in data science, with a focus on prici

Job Description We are seeking a highly skilled Lead Data Scientist with experience in pricing optimization, pricing elasticity, and AWS SageMaker. The ideal candidate will have a strong foundation in Statistics and Machine Learning, with a particular focus on Bayesian modeling. As part of our Data Science team, you will work closely with clients to develop advanced pricing strategies using state-of-the-art tools and techniques, including AWS SageMaker, to optimize business outcomes. Key Responsibilities: Lead and contribute to the development of pricing optimization models, leveraging statistical and machine learning techniques to inform strategic decisions. Analyze pricing elasticity to predict consumer response to changes in price, helping clients maximize revenue and market share. Implement and deploy machine learning models using AWS SageMaker for scalable and efficient performance in a cloud environment. Utilize Bayesian modeling to support decision-making processes, providing insights into uncertainty and model predictions. Collaborate with cross-functional teams to integrate data-driven insights into business processes. Communicate complex results and findings in a clear and concise manner to both technical and non-technical stakeholders. Continuously explore and experiment with new modeling approaches and tools to improve accuracy and efficiency of pricing solutions. Qualifications Bachelor s or Master s degree in Data Science, Statistics Mathematics Economics, or a related field. Advanced degrees preferred. 7+ years of hands-on experience in data science, with a focus on prici