1577 Data Scientist Jobs - Page 14

Data Scientist Hyderabad, 3 days WFO Highly skilled data scientist who will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. 4 to 7 years (II) of proven experience as a Data Scientist or in a similar role. Collaborate with AI/ML engineers, and architects to research, design, develop, and evaluate cutting-edge AI & generative AI models Build Train & Deploy AI Models to address real-world challenges Expertise working on AI platforms such as Dataiku, AWS Sagemaker, Bedrock, Snowflake Cortex AI etc. Interact with customers directly to understand the business problem, help and aid them in implementation of AI & generative AI solutions, deliver briefing and deep dive sessions to customers and guide customers on adoption patterns and paths to production Create and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations adapted to technical, business, and executive stakeholders Provide customer and market feedback to Product and Engineering teams to help define product direction Strong communication and client-facing skills, with the ability to translate technical concepts into business terms.

Develop and implement predictive models and machine learning algorithms to solve logistics-related problems such as demand forecasting , route optimization , inventory prediction , and shipment delay analysis . Analyze large volumes of structured and unstructured logistics data from systems such as TMS (Transportation Management Systems) , WMS (Warehouse Management Systems) , and ERP platforms . Design and maintain dashboards and visualizations to track supply chain KPIs, operational performance, and model outputs using Power BI , Tableau , or similar tools. Work cross-functionally with logistics, operations, procurement, and IT teams to understand business challenges and translate them into data science solutions. Use SQL , Python , R*, and big data tools* to extract, clean, and prepare datasets for analysis and modeling. Deploy models into production and monitor their performance to ensure accuracy and reliability over time. Contribute to strategic initiatives such as logistics network design, warehouse automation, and sustainability optimization. Conduct A/B testing and causal inference to evaluate changes in supply chain processes and logistics strategies Job Type: Full-time Pay: ₹800,000.00 - ₹1,200,000.00 per year Benefits: Health insurance Provident Fund Schedule: Day shift Work Location: In person

At AryaXAI , we’re building the future of explainable, scalable, and aligned AI —designed specifically for high-stakes environments where trust, transparency, and performance are non-negotiable. From financial services to energy and other regulated industries, our platform powers intelligent decision-making through safe and robust AI systems. We’re looking for a Data Scientist with a deep understanding of both classical and deep learning techniques, experience building enterprise-scale ML pipelines, and the ambition to tackle real-world, high-impact problems. You will work at the intersection of modeling, infrastructure, and regulatory alignment—fine-tuning models that must be auditable, performant, and production-ready. Responsibilities: Modeling & AI Development Design, build, and fine-tune machine learning models (both classical and deep learning) for complex mission-critical use cases in domains like banking, finance, energy, etc. Work on supervised, unsupervised, and semi-supervised learning problems using structured, unstructured, and time-series data. Fine-tune foundation models for specialized use cases requiring high interpretability and performance. Platform Integration Develop and deploy models on AryaXAI’s platform to serve real-time or batch inference needs. Leverage explainability tools (e.g., DLBacktrace, SHAP, LIME, or AryaXAI’s native xai_evals stack) to ensure transparency and regulatory compliance. Design pipelines for data ingestion, transformation, model training, evaluation, and deployment using MLOps best practices. Enterprise AI Architecture Collaborate with product and engineering teams to implement scalable and compliant ML pipelines across cloud and hybrid environments. Contribute to designing secure, modular AI workflows that meet enterprise needs—latency, throughput, auditability, and policy constraints. Ensure models meet strict regulatory and ethical requirements (e.g., bias mitigation, traceability, explainability). Requirements : 3+ years of experience building ML systems in production, ideally in regulated or enterprise environments. Strong proficiency in Python , with experience in libraries like scikit-learn, XGBoost, PyTorch, TensorFlow , or similar. Experience with end-to-end model lifecycle : from data preprocessing and feature engineering to deployment and monitoring. Deep understanding of enterprise ML architecture —model versioning, reproducibility, CI/CD for ML, and governance. Experience working with regulatory, audit, or safety constraints in data science or ML systems. Familiarity with ML Ops tools (MLflow, SageMaker, Vertex AI, etc.) and cloud platforms (AWS, Azure, GCP). Strong communication skills and an ability to translate technical outcomes into business impact. Bonus Points For Prior experience in regulated industries : banking, insurance, energy, or critical infrastructure. Experience with time-series modeling , anomaly detection, underwriting, fraud detection or risk scoring systems. Knowledge of RAG architectures , generative AI , or foundation model fine-tuning . Exposure to privacy-preserving ML , model monitoring , and bias mitigation frameworks. What You’ll Get Competitive compensation with performance-based upside Comprehensive health coverage for you and your family Opportunity to work on mission-critical AI systems where your models drive real-world decisions Ownership of core components in a platform used by top-tier enterprises Career growth in a fast-paced, high-impact startup environment Remote-first, collaborative, and high-performance team culture If you’re excited to build data science solutions that truly matter , especially in the most demanding industries, we want to hear from you.

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. United Health Group is a leading health care company serving more than 85 million people worldwide. The organization is ranked 5th among Fortune 500 companies. UHG serves its customers through two different platforms - United Health Care (UHC) and Optum. UHC is responsible for providing healthcare coverage and benefits services, while Optum provides information and technology enabled health services. India operations of UHG are aligned to Optum. The Optum Global Analytics Team, part of Optum, is involved in developing broad-based and targeted analytics solutions across different verticals for all lines of business. Primary Responsibilities Work on business analysis requests around different business problems Creating analytical findings for the internal clients of UHG as per specifications received from them using information in UHG Specific databases Work with Senior team members to develop new capabilities for the team Being Accountable Possess Achievable Drive Passionate about solution or product development Looks forward to build and apply technical and functional skills Focuses on understanding Goals, Priorities and Plans Possess problem solving approach Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications Bachelors or 4+ years of university degree 2+ years of Experience with below mentioned Skills 2+ years of business experience in analytics, machine learning projects in Business Intelligence/Business Analysis space Experience of GenAI with advanced artificial intelligence technologies and methodologies End to end experience in designing and deploying models and look out end to end productionize pipeline Good knowledge around Predictive & Prescriptive Analytics techniques like Hypothesis testing, Probability, Supervised & Unsupervised Learnings Good understanding of analytics tools: R, Python, SQL, Databricks & cloud technologies Deep understanding on Responsible use of AI Understanding on bias detection and mitigation strategy Processing and good to have fundamental understanding on Gen-AI & Large Language Models Proven solid problem-solving skills Proven excellent understanding of basic statistics and advance mathematics to analyze and understand data patterns Proven ability to learn and adapt to new data technologies Proven ability in slicing and dicing of data structures, Natural Language Proven good problem-solving & communication skills Preferred Qualifications Certified in Azure Cloud (AZ-900) Proven excellent time management & communication skills At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes — an enterprise priority reflected in our mission.

Job Title: Data Scientist – AIML, GenAI & Agentic AI Location: Pune/ Bangalore/ Indore/ Kolkata Job Type: Full-time Experience Level: 4+ Years NP : Immediate Joiner OR15 Days Max Job Description We are seeking a highly skilled and innovative Data Scientist / AI Engineer with deep expertise in AI/ML, Generative AI, and Agentic AI frameworks to join our advanced analytics and AI team. The ideal candidate will possess a robust background in data science and machine learning, along with hands-on experience in building and deploying end-to-end intelligent systems using modern AI technologies including RAG (Retrieval-Augmented Generation), LLMs, and agent orchestration tools. Key Responsibilities Design, build, and deploy machine learning models and Generative AI solutions for a wide range of use cases (text, vision, and tabular data). Develop and maintain AI/ML pipelines for large-scale training and inference in production environments. Leverage frameworks such as LangChain, LangGraph, CrewAI for building Agentic AI workflows. Fine-tune and prompt-engineer LLMs (e.g., GPT, BERT) for enterprise-grade RAG and NLP solutions. Collaborate with business and engineering teams to translate business problems into AI/ML models that deliver measurable value. Apply advanced analytics techniques such as regression, classification, clustering, sequence modeling, association rules, computer vision, and NLP. Architect and implement scalable AI solutions using Python , PyTorch , TensorFlow , and cloud-native technologies. Ensure integration of AI solutions within existing enterprise architecture using containerized services and orchestration (e.g., Docker, Kubernetes). Maintain documentation and present insights and technical findings to stakeholders. Required Skills and Qualifications Bachelor’s/Master’s/PhD in Computer Science, Data Science, Statistics, or related field. Strong proficiency in Python and libraries such as Pandas, NumPy, Scikit-learn, etc. Extensive experience with deep learning frameworks : PyTorch and TensorFlow. Proven experience with Generative AI , LLMs , RAG , BERT , and related architectures. Familiarity with LangChain , LangGraph , and CrewAI and strong knowledge of agent orchestration and autonomous workflows. Experience with large-scale ML pipelines , MLOps practices, and cloud platforms (AWS, GCP, or Azure). Deep understanding of software engineering principles , design patterns, and enterprise architecture. Strong problem-solving, analytical thinking, and debugging skills. Excellent communication, presentation, and cross-functional collaboration abilities. Preferred Qualifications Experience in fine-tuning LLMs and optimizing prompt engineering techniques. Publications, open-source contributions, or patents in AI/ML/NLP/GenAI. Experience with vector databases and tools such as Pinecone, FAISS, Weaviate, or Milvus. Why Join Us? Work on cutting-edge AI/ML and GenAI innovations. Collaborate with top-tier scientists, engineers, and product teams. Opportunity to shape the next generation of intelligent agents and enterprise AI solutions. Flexible work arrangements and continuous learning culture. To Apply: Please submit your resume and portfolio of relevant AI/ML work (e.g., GitHub, papers, demos) to Shanti.upase@calsoftinc.com

Job Description: RWE generation acts as the critical bridge from clinical effectiveness to a commercially viable brand. At MC Analytics, clinical and commercial disciplines work together, sharing insights and knowledge. It is never too early to consider commercialization in the drug development process. That’s why we are committed to working with you to design, develop and deliver fully integrated Real World Evidence ready for the peri-approval setting that collects the right data to ensure launch success. Desired Qualification & Skills : · 3+ years of hands-on experience in Data Science/Engineering. · Strong proficiency in R and/or Python programming, along with solid command-line skills. · Proficiency in building and maintaining ETL pipelines. · Experiences on building data models, data harmonization and quality control · Good understanding of the Healthcare domain. · Knowledge of OMOP and/or CDISC standards (STDM, ADaM) (preferred) · Strong communication and interpersonal skills, a detail-oriented approach, a problem-solving mindset, and the ability to learn quickly. · Prior experience in statistical programming, genomic data analysis, NLP applications on healthcare datasets and data visualization would be a valuable asset.

Skill Data Science - AI Data Science - ML Minimum Qualification B.Tech/B.E CERTIFICATION No data available Working Language English Job Description Data Analyst with AI/ML expertise responsible for leveraging advanced data analytics, statistical techniques, and machine learning (ML) methodologies to provide actionable insights, optimize business processes, and support data-driven decision-making. The role requires strong collaboration with IT leadership to align analytics initiatives with organizational goals, as well as mentoring junior team members in data analysis and AI/ML practices

Role & responsibilities Role Overview We are seeking a Senior Associate Data Science/ML/DL/GenAI to join our high-impact, entrepreneurial team. This individual will play a key role in designing and delivering scalable AI applications, conducting applied research in GenAI and deep learning, and contributing to the team’s innovation agenda. This is a hands-on, technical role ideal for professionals passionate about AI-driven transformation. Key Responsibilities Design, develop, and deploy machine learning, deep learning, and Generative AI solutions tailored to business use cases. Build scalable pipelines using Python (and frameworks such as Flask/FastAPI) to operationalize data science models in production environments. Prototype and implement solutions using state-of-the-art LLM frameworks such as LangChain, LlamaIndex, LangGraph, or similar. Also developing applications in streamlit/chainlit for demo purposes. Design advanced prompts and develop agentic LLM applications that autonomously interact with tools and APIs. Fine-tune and pre-train LLMs (HuggingFace and similar libraries) to align with business objectives. Collaborate in a cross-functional setup with ML engineers, architects, and product teams to co-develop AI solutions. Conduct R&D in NLP, CV, and multi-modal tasks, and evaluate model performance with production-grade metrics. Stay current with AI research and industry trends; continuously upskill to integrate the latest tools and methods into the team’s work. Required Skills & Experience 4 to 6 years of experience in Data Science/ML/AI roles. Bachelor’s degree in Computer Science, Engineering, or equivalent technical discipline (BE/BTech/MCA). Proficiency in Python and related data science libraries: Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, PyTorch, Keras, etc. Hands-on experience with Generative AI , including prompt engineering, LLM fine-tuning, and deployment. Experience with Agentic LLMs and task orchestration using tools like LangGraph or AutoGPT-like flows. Strong knowledge of NLP techniques, transformer architectures, and text analysis. Proven experience working with cloud platforms (preferably Azure; AWS/GCP also considered). Understanding of production-level AI systems including CI/CD, model monitoring, and cloud-native architecture. (Need not develop from scratch) Familiarity with ML algorithms: XGBoost, GBM, k-NN, SVM, Decision Forests, Naive Bayes, Neural Networks, etc. Exposure to deploying AI models via APIs and integration into larger data ecosystems. Strong understanding of model operationalization and lifecycle management. Good to Have Experience with Docker, Kubernetes, and containerized deployments for ML workloads. Use of MLOps tooling and pipelines (e.g., MLflow, Azure ML, SageMaker, etc.). Experience in full-stack AI applications, including visualization (e.g., PowerBI, D3.js). Demonstrated track record of delivering AI-driven solutions as part of large-scale systems. Soft Skills & Team Expectations Strong written and verbal communication; able to explain complex models to business stakeholders. Ability to independently document work, manage requirements, and self-drive technical discovery. Desire to innovate, improve, and automate existing processes and solutions. Active contributor to team knowledge sharing, technical forums, and innovation drives. Strong interpersonal skills to build relationships across cross-functional teams. A mindset of continuous learning and technical curiosity. Preferred Certifications (at least two are preferred) Certifications in Machine Learning, Deep Learning, or Natural Language Processing. Python programming certifications (e.g., PCEP/PCAP). Cloud certifications (Azure/AWS/GCP) such as Azure AI Engineer, AWS ML Specialty, etc. Why Join PwC CTIO? Be part of a mission-driven AI innovation team tackling industry-wide transformation challenges. Gain exposure to bleeding-edge GenAI research, rapid prototyping, and product development. Contribute to a diverse portfolio of AI solutions spanning pharma, finance, and core business domains. Operate in a startup-like environment within the safety and structure of a global enterprise. Accelerate your career as a deep tech leader in an AI-first future. Shift:11am-8pm

Make an impact with NTT DATA Join a company that is pushing the boundaries of what is possible. We are renowned for our technical excellence and leading innovations, and for making a difference to our clients and society. Our workplace embraces diversity and inclusion – it’s a place where you can grow, belong and thrive. Your day at NTT DATA The Senior Data Scientist is an advanced subject matter expert, tasked with taking accountability in the adoption of data science and analytics within the organization. The primary responsibility of this role is to participate in the creation and delivery of data-driven solutions that add business value using statistical models, machine learning algorithms, data mining, and visualization techniques. What You'll Be Doing Key Responsibilities: Designs, develops, and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement. Designs and enhances data collection procedures to include information that is relevant for building analytic systems. Responsible for ensuring that data used for analysis is processed, cleaned and, integrally verified and build algorithms necessary to find meaningful answers. Designs and codes software programs, algorithms, and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources Provides meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers. Directs scalable and highly available applications leveraging the latest tools and technologies. Accountable for creatively visualizing and effectively communicating results of data analysis, insights, and ideas in a variety of formats to key decision-makers within the business. Creates SQL queries for the analysis of data and visualizes the output of the models. Responsible for ensuring that industry standards best practices are applied to development activities. Knowledge and Attributes: Advanced understanding of data modelling, statistical methods and machine learning techniques. Strong ability to thrive in a dynamic, fast-paced environment. Strong quantitative and qualitative analysis skills. Desire to acquire more knowledge to keep up to speed with the ever-evolving field of data science. Curiosity to sift through data to find answers and more insights. Advanced understanding of the information technology industry within a matrixed organization and the typical business problems such organizations face. Strong ability to translate technical findings clearly and fluently to non-technical team business stakeholders to enable informed decision-making. Strong ability to create a storyline around the data to make it easy to interpret and understand. Self-driven and able to work independently yet acts as a team player. Academic Qualifications and Certifications: Bachelor’s degree or equivalent in Data Science, Business Analytics, Mathematics, Economics, Engineering, Computer Science or a related field. Relevant programming certification preferred. Agile certification preferred. Required Experience: Advanced demonstrated experience in a data science position in a corporate environment and/or related industry. Advanced demonstrated experience in statistical modelling and data modelling, machine learning, data mining, unstructured data analytics, natural language processing. Advanced demonstrated experience in programming languages (R, Python, etc.). Advanced demonstrated experience working with and creating data architectures. Advanced demonstrated experience with extracting, cleaning, and transforming data and working with data owners to understand the data. Advanced demonstrated experience visualizing and/or presenting data for stakeholder use and reuse across the business. Workplace type: Hybrid Working About NTT DATA NTT DATA is a $30+ billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long-term success. We invest over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure, and connectivity. We are also one of the leading providers of digital and AI infrastructure in the world. NTT DATA is part of NTT Group and headquartered in Tokyo. Equal Opportunity Employer NTT DATA is proud to be an Equal Opportunity Employer with a global culture that embraces diversity. We are committed to providing an environment free of unfair discrimination and harassment. We do not discriminate based on age, race, colour, gender, sexual orientation, religion, nationality, disability, pregnancy, marital status, veteran status, or any other protected category. Join our growing global team and accelerate your career with us. Apply today.

PwC AC is hiring for Data scientist Apply and get a chance to work with one of the Big4 companies #PwC AC. Job Tit le : Data scientist Years of Experienc e: 4+ years Shift Timin gs: 2PM-11PM Qualificati on: Graduate and above(Full time) About PwC CTIO – AI Engineering PwC’s Commercial Technology and Innovation Office (CTIO) is at the forefront of emerging technology, focused on building transformative AI-powered products and driving enterprise innovation. The AI Engineering team within CTIO is dedicated to researching, developing, and operationalizing cutting-edge technologies such as Generative AI, Large Language Models (LLMs), AI Agents, and more. Our mission is to continuously explore what's next—enabling business transformation through scalable AI/ML solutions while remaining grounded in research, experimentation, and engineering excellence. Role Overview We are seeking a Senior Associate – Data Science/ML/DL/GenAI to join our high-impact, entrepreneurial team. This individual will play a key role in designing and delivering scalable AI applications, conducting applied research in GenAI and deep learning, and contributing to the team’s innovation agenda. This is a hands-on, technical role ideal for professionals passionate about AI-driven transformation. Key Responsibilities Design, develop, and deploy machine learning, deep learning, and Generative AI solutions tailored to business use cases. Build scalable pipelines using Python (and frameworks such as Flask/FastAPI) to operationalize data science models in production environments. Prototype and implement solutions using state-of-the-art LLM frameworks such as LangChain, LlamaIndex, LangGraph, or similar. Also developing applications in streamlit/chainlit for demo purposes. Design advanced prompts and develop agentic LLM applications that autonomously interact with tools and APIs. Fine-tune and pre-train LLMs (HuggingFace and similar libraries) to align with business objectives. Collaborate in a cross-functional setup with ML engineers, architects, and product teams to co-develop AI solutions. Conduct R&D in NLP, CV, and multi-modal tasks, and evaluate model performance with production-grade metrics. Stay current with AI research and industry trends; continuously upskill to integrate the latest tools and methods into the team’s work. Required Skills & Experience 4 to 9 years of experience in Data Science/ML/AI roles. Bachelor’s degree in Computer Science, Engineering, or equivalent technical discipline (BE/BTech/MCA). Proficiency in Python and related data science libraries: Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, PyTorch, Keras, etc. Hands-on experience with Generative AI , including prompt engineering, LLM fine-tuning, and deployment. Experience with Agentic LLMs and task orchestration using tools like LangGraph or AutoGPT-like flows. Strong knowledge of NLP techniques, transformer architectures, and text analysis. Proven experience working with cloud platforms (preferably Azure; AWS/GCP also considered). Understanding of production-level AI systems including CI/CD, model monitoring, and cloud-native architecture. (Need not develop from scratch) Familiarity with ML algorithms: XGBoost, GBM, k-NN, SVM, Decision Forests, Naive Bayes, Neural Networks, etc. Exposure to deploying AI models via APIs and integration into larger data ecosystems. Strong understanding of model operationalization and lifecycle management. Good to Have Experience with Docker, Kubernetes, and containerized deployments for ML workloads. Use of MLOps tooling and pipelines (e.g., MLflow, Azure ML, SageMaker, etc.). Experience in full-stack AI applications, including visualization (e.g., PowerBI, D3.js). Demonstrated track record of delivering AI-driven solutions as part of large-scale systems. Soft Skills & Team Expectations Strong written and verbal communication; able to explain complex models to business stakeholders. Ability to independently document work, manage requirements, and self-drive technical discovery. Desire to innovate, improve, and automate existing processes and solutions. Active contributor to team knowledge sharing, technical forums, and innovation drives. Strong interpersonal skills to build relationships across cross-functional teams. A mindset of continuous learning and technical curiosity. Preferred Certifications (at least two are preferred) Certifications in Machine Learning, Deep Learning, or Natural Language Processing. Python programming certifications (e.g., PCEP/PCAP). Cloud certifications (Azure/AWS/GCP) such as Azure AI Engineer, AWS ML Specialty, etc. Why Join PwC CTIO? Be part of a mission-driven AI innovation team tackling industry-wide transformation challenges. Gain exposure to bleeding-edge GenAI research, rapid prototyping, and product development. Contribute to a diverse portfolio of AI solutions spanning pharma, finance, and core business domains. Operate in a startup-like environment within the safety and structure of a global enterprise. Accelerate your career as a deep tech leader in an AI-first future.

* Strong programming skills in Python, including knowledge of libraries like NumPy, Pandas, Matplotlib, and Seaborn. * Proficiency in AI/ML frameworks: scikit-learn, TensorFlow, Keras, or PyTorch. *LLM

And because our technology is purpose-built for restaurants, by restaurant people, restaurants can trust that well deliver on their needs for today while investing in experiences that will power their restaurant of the future, Breadyto make a change Toast is looking to expand the Data Science team to deliver new Data Science models to meet Toast Capital/Lending increased demands As a Principal Data Scientist, you will bring senior data science technical leadership with domain expertise in lending to the Capital Data Science team An ideal candidate has wealth of experience in banking lending technology or a leading fintech company with substantial depth of expertise and knowledge in lending underwriting, and risk management models, About this Roll*: Lead the development and implementation of advanced predictive models, to assess credit risk, optimize lending growth, and improve overall portfolio performance, Will actively engage in code reviews and comprehensive data quality assessments, ensuring that all development data pipelines and code meet the highest standards of reliability, accuracy, and readiness for seamless production deployment Collaborate closely with cross-functional teams, including Risk Management, Product, Engineering, and Business Strategy, to identify opportunities for leveraging data-driven insights to support growth and risk mitigation initiatives, Design, develop, and maintain innovative credit risk and lending growth strategies that align with the organization's objectives, while ensuring compliance with regulatory requirements and industry best practices, Monitor and analyze the performance of existing models and strategies, identifying areas for improvement and implementing data-driven refinements as needed, Present complex data-driven insights and recommendations to stakeholders in a clear, concise, and actionable manner, while fostering a data-driven culture within the organization, Mentor and guide junior data scientists, fostering a collaborative environment and promoting the growth and development of the data science team, Stay current with the latest trends and developments in data science, fintech, and credit risk management, continually exploring new methods and technologies to enhance the organization's capabilities, Do you have the right ingredients* Advanced degree in quantitative field such as Data Science, Statistics, Mathematics, Financial Engineering or related discipline 10+ years of experience in data science, with a focus on credit risk modeling in retail lending space (consumer or small business) and lending growth strategies, preferably within the fintech lending space, Proficiency in machine learning, AI, and statistical modeling techniques, with a strong track record of developing and deploying successful predictive models in a business setting, Familiarity with the US model risk management policies such as SR 11-7 that govern the lending models is strongly preferred, Strong proficiency in Python and SQL and experience with data science libraries and tools such as: Spark, Scala, scikit-learn, Tensorflow, PyTorch, XGBoost etc Familiarity with standard software engineering practices and tools including object-oriented programming, test-driven development, CI/CD, git, task orchestration (Airflow) and AWS tooling Strong understanding of credit risk management, lending practices, and regulatory requirements within the financial industry, Excellent communication and presentation skills, with the ability to articulate complex data-driven insights to both technical and non-technical stakeholders, Strong leadership skills, with experience mentoring and guiding junior data scientists Bonus ingredients*: Passion for research and curiosity that calls you to go beyond good enough to create something innovative and exciting Self starter who loves to dig into different kinds of data to solve business problems and can communicate their findings to cross-functional stakeholders Work Mode: This role follows a hybrid work model, requiring a minimum of 2 days per week in the office, Diversity, Equity, and Inclusion is Baked into our Recipe for Success At Toast, our employees are our secret ingredientwhen they thrive, we thrive The restaurant industry is one of the most diverse, and we embrace that diversity with authenticity, inclusivity, respect, and humility By embedding these principles into our culture and design, we create equitable opportunities for all and raise the bar in delivering exceptional experiences, We Thrive Together We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs Our goal is to build a strong culture of connection as we work together to empower the restaurant community To learn more about how we work globally and regionally, check out: https://careers toasttab,/locations-toast, Apply today! Toast is committed to creating an accessible and inclusive hiring process As part of this commitment, we strive to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process

We are seeking a Senior Data Scientist with strong engineering skills and hands-on experience in Python , FastAPI , and asynchronous programming , along with a deep understanding of LLM orchestration frameworks like LangChain and LangGraph . The ideal candidate should have proven experience designing and deploying agentic AI systems using frameworks such as A2A and CrewAI . This role combines data science expertise with backend development and generative AI innovations, driving impactful solutions across domains. Key Responsibilities: Design and deploy intelligent applications using LLMs with LangChain and LangGraph. Build and orchestrate agentic workflows using A2A, CrewAI, or similar frameworks. Develop robust, scalable APIs using FastAPI and async programming. Implement end-to-end pipelines that integrate AI agents with external APIs, databases, and tools. Conduct prompt engineering, memory management, retrieval augmentation, and tool integration. Evaluate and improve model performance through experimentation and fine-tuning. Collaborate with ML engineers, product managers, and backend developers to deliver AI-powered features. Stay abreast of the latest advancements in the LLM, agentic AI, and multi-agent system space. Required Skills & Experience: Strong Python programming expertise (6+ years). Experience building REST APIs with FastAPI and handling async/await operations. Deep understanding of LLM frameworks like LangChain , LangGraph , or custom agent frameworks. Experience with multi-agent orchestration frameworks like AutoGen , A2A , CrewAI , etc. Experience in prompt engineering , RAG (retrieval-augmented generation) , and vector DBs (e.g., FAISS, Pinecone). Good grasp of architectural patterns for scalable AI applications. Knowledge of common LLM APIs (e.g., OpenAI, Anthropic, Cohere).

The Lead data Scientist will be responsible for organizing and reporting data related to sales numbers, market research, logistics, linguistics, or other behaviors. They utilize technical expertise to ensure data reported is accurate and high-quality. Data will need to be analysed, designed, and presented in a way that assists individuals, business owners and customer stakeholders to make better decisions. Responsibilities: Cross-Functional Collaboration: Collaborate seamlessly with Engineering, Product, and Operations teams to conceptualise, design, and construct data reporting and analytical systems. Ideation and Analysis: Generate ideas for exploratory analysis, actively shaping the trajectory of future projects. Provide insightful recommendations for strategic actions based on data-driven insights. Rapid Prototyping and Product Discussions: Drive the rapid prototyping of solutions, actively participating in discussions related to product and feature development. Dashboard Creation and Reporting: Develop dashboards and comprehensive documentation to effectively communicate results. Regularly monitor key data metrics, facilitating informed decision-making. Integration with Production Systems: Collaborate closely with software engineers to deploy and integrate data models into production systems. Ensure scalability, reliability, and efficiency of integrated solutions. Business Metrics Identification: Identify and analyze key business metrics, offering strategic insights. Recommend product features based on the identified metrics to enhance overall product functionality. Understand and manage Data Infrastructure: Lead the design and development of scalable, robust, and efficient data architectures. Oversee the development and maintenance of ETL (Extract, Transform, Load) processes to move and transform data from various sources into data warehouses or other storage solutions. Ensure data quality and integrity throughout the data pipeline. Team Leadership: Lead a team of data engineers and data analysts, providing mentorship, guidance, and technical expertise. Coach and manage a team to deliver using Agile processes and ensure high RoI. Participating actively in recruitment and nurturing of engineers as awesome as you. Skills Exceptional quantitative and problem-solving skills - capable of tackling complex data-driven challenges and formulating effective solutions. Proven proficiency - In essential data science libraries, including Pandas, Numpy, SciPy, and Scikit-Learn, for data manipulation, analysis, and modeling. In-depth expertise in Python programming and SQL - Focus on data analysis, model building, and algorithmic implementation. Experience with distributed computing frameworks - Hadoop or Spark, for handling large-scale data processing and machine learning tasks. Data Architecture - Designing and implementing robust data architectures that support the organizations needs. This includes understanding different database systems, data lakes, and data warehouses.

Build and deploy machine learning models that deliver business impact Develop frameworks to monitor and ensure fairness in our AI systems Analyze large, complex datasets to uncover insights and power product decisions Collaborate with cross-functional teams to translate models into production Push the boundaries of applied ML and Responsible AI Experience with Python and ML libraries (eg, scikit-learn, PyTorch, TensorFlow) Experience our comprehensive benefits with family medical, vision and dental coverage, a competitive base salary, and eligibility for equity awards and discretionary bonuses or commissions

You will be contributing towards building Forecasting / Prediction / Root-cause algorithms/AgenticAI/Vision algorithms by closely collaborating across teams and provide solution to business challenges. In most cases the prioritization of business challenges is based on impact and hence your contributions can have direct impact to our businesses. What you'll do: 1. Play a key role to solve complex AI problems, pivotal to Walmart s business and drive actionable insights from terabytes of data 2. Leverage data science tools and techniques, keeping abreast with the latest in the community to solve problems for Walmart at Scale and take them to PROD using best industry standard practices. 3. Develop ideas leveraging GenAI, Agentic AI and take them to PROD 4. Take forward the solutions into Pipelines/APIs into PROD as needed by the business 5. Research, learn/disseminate & adapt new technologies to solve problems & improve upon existing solutions 6. Brainstorm, review and mentor junior associates in providing robust data science solutions What you'll bring: M.Tech with 5+ years of relevant experience in Machine learning / Artificial intelligence Problem solver at heart with experience in taking solutions to PROD Proficiency with Python/Java/PySpark/BiqQuery etc Proficiency with ML libraries sklearn/pytorch/tensorflow etc Good knowledge of commonly used design patterns in data science Cloud friendliness (GCP/Azure etc) to leverage distributed computing/scalability Good communication / influencing / mentoring skills with inclination to high ownership and commitment Minimum Qualifications... Minimum Qualifications:Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years experience in an analytics related field. Option 3: 6 years experience in an analytics or related field. Preferred Qualifications... Masters degree in Computer Science, Computer Engineering, Computer Information Systems, Software Engineering, or related area and 2 years experience in software engineering or related area

You will be at the forefront of dunnhumby s research data science team where you will be translating a complex business problem into a data science problem and solving that with scalable and state-of-the art AI algorithms. Joining our research data science team, you will be helping identify new opportunities within the Data Science space for future dunnhumby solutions. Learn from experts and grow your career in our organisation What we expect from you Degree or equivalent in a statistical or mathematical subject. 5 to 7 Years of experience in Data Science Good understanding of statistics and mathematical methodologies used - especially forecasting, regression, linear models, time series, hypothesis tests and optimisation Ability to prototype solutions using Python and Spark to facilitate development and testing of algorithms on large data sets Good understanding of machine learning techniques, with applications to classification, prediction and clustering Ability to apply and extend experimental design methodology to conduct rigorous measurement of treatment effects Good working knowledge of databases, including SQL, relational and non-relational data models Experience of using following algorithm at scale: Ancova, linear models with regularization, clustering, random forests, xgboost Research the latest machine learning approaches Good grasp of Object-Oriented Programming Stakeholder Management Ability to quickly learn open-source statistics and machine learning packages - Pandas, SciPy, Scikit - learning, Tensor flow. Experience in developing solutions related to Market Mix Modelling, Causal AI and Generative AI

Job Description About Signify Through bold discovery and cutting-edge innovation, we lead an industry that is vital for the future of our planet: lighting Through our leadership in connected lighting and the Internet of Things, we're breaking new ground in data analytics, AI, and smart solutions for homes, offices, cities, and beyond, At Signify, you can shape tomorrow by building on our incredible 125+ year legacy while working toward even bolder sustainability goals Our culture of continuous learning, creativity, and commitment to diversity and inclusion empowers you to grow your skills and career, Join us, and together, well transform our industry, making a lasting difference for brighter lives and a better world You light the way, More About The Role Were looking for a Data Scientist to work on Deep learning, machine learning, data mining, and statistical modelingfor providing predictive and prescriptive enterprise analytics Successful candidates will be expected to guide a team of Data Scientists, investigate state of the art techniques in advanced machine learning and statistical modeling, and design, develop, and deploy state-of-art, scalable systems for innovative analytics applications across various functional areas (e-g Finance, Sales, Marketing, Supply Chain, etc ) Applicants will be expected to work with a diverse set of data sources, such as time series data, graph data, semi-structured and unstructured data, and build statistical / machine-learning / Deep Learning/Gen AI models in support of on-demand, real-time analytic services The applicant should also have strong skills in explaining the analytic models and outcomes to business stakeholders, Youll be part of the Signifys Enterprise Data & Analytics team, based in Bangalore, More About You Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field 4+ years of hands-on experience in data science or a related field with demonstrated history of delivering analytics models and solutions Strong programming skills in Python, PySpark or other statistical programming languages Strong foundation in machine learning and deep learning algorithms and expertise in natural language processing (NLP) and computer vision techniques Experience with popular deep learning frameworks such as TensorFlow and PyTorch Research and explore the latest advancements in generative AI, including techniques like natural language processing (NLP), computer vision, and machine learning Develop and implement generative AI models and algorithms to address specific business challenges Train and fine-tune generative AI models using large datasets and industry-specific knowledge to improve accuracy and efficiency Knowledge of cloud platforms like AWS, GCP, or Azure Strong problem-solving skills, communication skills and the ability to think creatively and strategically with a focus on business outco Everything well do for you Opportunity to work on some of the highly complex and challenging business problems across a variety of functional and business domains, Competitive salary depending on experience, Extensive set of tools to drive your career, such as a personalized learning platform, training and coaching You can grow a lasting career here Well encourage you, support you, and challenge you Well help you learn and progress in a way thats right for you, with coaching and mentoring along the way Well listen to you too, because we see and value every one of our 30,000+ people, We believe that a diverse and inclusive workplace fosters creativity, innovation, and a full spectrum of bright ideas With a global workforce representing 99 nationalities, we are dedicated to creating an inclusive environment where every voice is heard and valued, helping us all achieve more together,

Curious about the role ? Generative AI & NLP Development : Design, develop, and deploy advanced applications and solutions using Generative AI models (e.g., GPT, LLaMA, Mistral) and NLP algorithms to solve business challenges and unlock new opportunities for our clients. Model Customization & Fine-Tuning: Apply state-of-the-art techniques like LoRA, PEFT, and fine-tuning of large language models to adapt solutions to specific use cases, ensuring high relevance and impact. Innovative Problem Solving : Leverage advanced AI methodologies to tackle real-world business problems, providing creative and scalable AI-powered solutions that drive measurable results. Data-Driven Insights: Conduct deep analysis of large datasets, uncovering insights and trends that guide decisionmaking, improve operational efficiencies, and fuel innovation. Cross-Functional Collaboration: Work closely with Consulting, Engineering, and other teams to integrate AI solutions into broader business strategies, ensuring the seamless deployment of AI-powered applications. Client Engagement: Collaborate with clients to understand their unique business needs, provide tailored AI solutions, and educate them on the potential of Generative AI to drive business transformation. What do we expect? Generative AI & NLP Expertise: Extensive experience in developing and deploying Generative AI applications and NLP frameworks, with hands-on knowledge of LLM fine-tuning, model customization, and AI-powered automation. Hands-On Data Science Experience: 6+ years of experience in data science, with a proven ability to build and operationalize machine learning and NLP models in real-world environments. AI Innovation: Deep knowledge of the latest developments in Generative AI and NLP, with a passion for experimenting with cutting-edge research and incorporating it into practical solutions. Problem-Solving Mindset: Strong analytical skills and a solution-oriented approach to applying data science techniques to complex business problems. Communication Skills: Exceptional ability to translate technical AI concepts into business insights and recommendations for non-technical stakeholders.

Are you passionate about solving complex logistics challenges? Our Analytics team is at the forefront of enhancing delivery experiences through data-driven solutions and innovative technology. As a Data Scientist, you will join a team dedicated to optimizing our delivery network, ensuring reliable and efficient service to our customers. We are seeking an enthusiastic, customer-centric professional with strong analytical capabilities to drive impactful projects, implement advanced solutions, and develop scalable processes. In this role, you will have immediate ownership of business-critical challenges and the opportunity to make strategic, data-driven decisions that shape the future of our delivery operations. Your work will directly influence customer experience and operational excellence. The ideal candidate will possess both research science capabilities and program management skills, thriving in an environment that requires independent decision-making and comfort with ambiguity. This role offers the opportunity to make a significant impact on our advanced logistics network while working with pioneering technology and data science applications. Basic qualifications 6+ years of building machine learning models for business application experience Knowledge of programming languages such as C/C++, Python, Java or Perl Experience programming in Java, C++, Python or related language Experience with neural deep learning methods and machine learning Preferred qualifications: PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field 7+ years of extensive relevant research experience Deep expertise in Machine Learning Proficiency in programming Core competency in mathematics and statistics Track record of successful projects in algorithm design and product development Publications at peer-reviewed conferences or journals Prior experience with mentorship and/or management of scientists Strategic thinker with good execution skills Exhibits excellent business judgment Effective verbal and written communication skills Experience working with real-world data sets and building scalable models from big data Experience with modern modeling tools and frameworks such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow Experience with large scale distributed systems 6+ years of building machine learning models for business application experience Knowledge of programming languages such as C/C++, Python, Java or Perl Experience programming in Java, C++, Python or related language Experience with neural deep learning methods and machine learning PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field 15+ years of relevant, broad research experience Deep expertise in Machine Learning Proficiency in programming core competency in mathematics and statistics. Track record of successful projects in algorithm design and product development. Publications at top-tier peer-reviewed conferences or journals. prior experience with mentorship and/or management of scientists Thinks strategically, but stays on top of tactical execution. Exhibits excellent business judgment; balances business Effective verbal and written communication skills Experience working with real-world data sets and building scalable models from big data. Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, Experience with large scale distributed systems

Essential Responsibilities: Architecture & Design Define and document the overall data platform architecture in GCP, including ingestion (Pub/Sub, Dataflow), storage (BigQuery, Cloud Storage), and orchestration (Composer, Workflows). Establish data modeling standards (star/snowflake schemas, partitioning, clustering) to optimize performance and cost. Platform Implementation Build scalable, automated ETL/ELT pipelines for IoT telemetry and events. Implement streaming analytics and CDC where required to support real-time dashboards and alerts. Data Products & Exchange Collaborate with data scientists and product managers to package curated datasets and ML feature tables as consumable data products. Architect and enforce a secure, governed data exchange layerleveraging BigQuery Authorized Views, Data Catalog, and IAMto monetize data externally. Cost Management & Optimization Design cost-control measures: table partitioning/clustering, query cost monitoring, budget alerts, and committed-use discounts. Continuously analyze query performance and storage utilization to drive down TCO. Governance & Security Define and enforce data governance policies (cataloging, lineage, access controls) using Cloud Data Catalog and Cloud IAM. Ensure compliance with privacy, security, and regulatory requirements for internal and external data sharing. Stakeholder Enablement Partner with business stakeholders to understand data needs and translate them into platform capabilities and SLAs. Provide documentation, training, and self-service tooling (Data Studio templates, APIs, notebooks) to democratize data access. Mentorship & Leadership Coach and mentor engineers on big data best practices, SQL optimization, and cloud-native architecture patterns. Lead architecture reviews, proof-of-concepts, and pilot projects to evaluate emerging technologies (e.g., BigQuery Omni, Vertex AI). What You'll Bring to Our Team Minimum Qualifications Bachelor’s degree in Computer Science, Engineering, or related field. 8+ years designing and operating large-scale data platforms, with at least 5 years hands-on experience in GCP (BigQuery, Dataflow, Pub/Sub). Deep expertise in BigQuery performance tuning, data partitioning/clustering, and cost-control techniques. Proven track record building streaming and batch pipelines (Apache Beam, Dataflow, Spark). Strong SQL skills and experience with data modeling for analytics. Familiarity with data governance tools: Data Catalog, IAM, VPC Service Controls. Experience with Python or Java for ETL/ELT development. Excellent communication skills, able to translate technical solutions for non-technical stakeholders.

Job Summary As a Data Scientist at Bluphlux, you will play a pivotal role in leveraging advanced data analytics and machine learning techniques to enhance our recruitment processes. You will work closely with our innovative team to develop and implement models that improve the accuracy and efficiency of candidate selection, ensuring that our clients receive the best possible matches for their job openings. Key Responsibilities Develop and implement machine learning models to improve recruitment processes. Analyze large datasets to extract meaningful insights and trends. Collaborate with cross-functional teams to integrate data-driven solutions into our recruitment platform. Continuously evaluate and refine algorithms to enhance performance and accuracy. Stay updated with the latest advancements in data science and machine learning to ensure our solutions remain cutting-edge. Required Qualifications Bachelors or Masters degree in Data Science, Computer Science, Statistics, or a related field. Proven experience as a Data Scientist or similar role. Strong proficiency in programming languages such as Python or R. Experience with machine learning frameworks and libraries. Excellent analytical and problem-solving skills. Preferred Skills Experience in the recruitment or HR tech industry. Familiarity with natural language processing (NLP) techniques. Knowledge of cloud platforms and big data technologies.

Job Title: Senior Data Scientist Location: Bangalore Experience: 8 - 12 Years Job Summary We are seeking a highly skilled and experienced Senior Data Scientist to join our team in Bangalore. The ideal candidate will have a deep understanding of Machine Learning (ML) and Artificial Intelligence (AI), with a strong focus on Azure Fabric within the banking and finance domain. In this role, you will develop and implement advanced data-driven solutions that enhance decision-making, optimise processes, and contribute to the success of our client s financial objectives. Mandatory Skills Proven experience in traditional Machine Learning (ML) and Artificial Intelligence (AI). Strong experience in Azure Fabric and its integration with various banking systems. Expertise in Data Science methodologies, predictive modelling, and statistical analysis. Solid understanding of the Finance domain with a focus on banking processes and challenges. Hands-on experience with big data technologies and cloud platforms (Azure, AWS). Proficiency in Python-related data science libraries (e.g., Pandas, NumPy, Scikit-learn). Experience in data processing, ETL pipelines, and data engineering. Familiarity with SQL and NoSQL databases. Key Responsibilities Design and implement Machine Learning (ML) and Artificial Intelligence (AI) models to solve complex business problems in the finance sector. Work closely with business stakeholders to understand requirements and translate them into data-driven solutions. Develop and deploy ML models on Azure Fabric, ensuring their scalability and efficiency. Analyze large datasets to identify trends, patterns, and insights to support decision-making. Collaborate with cross-functional teams to integrate AI/ML solutions into business processes and banking systems. Maintain and optimise deployed models and ensure their continuous performance. Keep up to date with industry trends, technologies, and best practices in AI and ML, specifically within the finance industry. Qualifications Education: Bachelor s/Master s degree in Computer Science, Data Science, Engineering, or related field. Certifications: Relevant certifications in Data Science, Azure AI, or Machine Learning is a plus. Technical Skills Expertise in Machine Learning (ML) algorithms (Supervised and Unsupervised). Strong experience with Azure Fabric and related Azure cloud services. Proficient in Python, R, and data science libraries (Pandas, Scikit-learn, TensorFlow). Experience in AI and Deep Learning models, including neural networks. Working knowledge of big data technologies such as Spark, Hadoop, and Databricks. Experience with version control systems (Git, GitHub, etc.). Soft Skills Excellent problem-solving and analytical skills. Strong communication skills, with the ability to present complex data insights clearly to non-technical stakeholders. Ability to work effectively in a collaborative, cross-functional environment. Strong attention to detail and ability to manage multiple tasks simultaneously. A passion for continuous learning and staying updated on new technologies. Experience in the banking or financial services industry. Familiarity with DevOps practices for ML/AI model deployment. Knowledge of cloud-native architecture and containerization (Docker, Kubernetes). Familiarity with Deep Learning and Natural Language Processing (NLP) techniques. 8-12 years of experience in Data Science, with hands-on experience in ML, AI, and working within the finance or banking industry. Proven track record of designing and deploying machine learning models and working with Azure Fabric. Experience with client-facing roles and delivering solutions that impact business decision-making. Competitive salary and annual performance-based bonuses Comprehensive health and optional Parental insurance. Retirement savings plans and tax savings plans. Work-Life Balance: Flexible work hours Timely and effective delivery of ML/AI models that solve complex business problems. Continuous improvement and optimisation of deployed models. High-quality insights and data-driven solutions delivered for business stakeholders. Client satisfaction with AI/ML solutions implemented within the banking domain. Number of successful ML/AI models deployed and their performance post-deployment. Model accuracy and predictive capability (based on business goals). Client feedback on AI-driven solutions. Completion time for delivering actionable data-driven insights. Team collaboration and mentoring effectiveness with junior data scientists. Click here to upload your CV / Resume We accept PDF, DOC, DOCX, JPG and PNG files Verification code successfully sent to registered email Invalid Verification Code! Thanks for the verification! Our support team will contact you shortly!.

Data Scientist II With over 140 million users, Junglee Games is a leader in the online skill gaming space. Founded in San Francisco in 2012 and part of the Flutter Entertainment Group, we are revolutionizing how people play games. Our notable games include Howzat, Junglee Rummy, and Junglee Poker. Our team comprises over 1000 talented individuals who have worked on internationally acclaimed AAA titles like Transformers and Star Wars: The Old Republic and contributed to Hollywood hits such as Avatar. Junglee s mission is to build entertainment for millions of people around the world and connect them through games. Junglee Games is not just a gaming company but a blend of innovation, data science, cutting-edge tech, and, most importantly, a values-driven culture that is creating the next set of conscious leaders. Job overview As a Data Scientist II / III, you will be responsible for solving complex business problems using advanced data science techniques. You will lead the design and development of machine learning models, conduct statistical analyses, and collaborate with cross-functional teams to drive actionable insights. Your role will include both technical hands-on work and mentorship of junior data scientists. Job Location : Gurgaon / Bengaluru Key Responsibilities Assist in the development and implementation of machine learning models and algorithms to address business problems, including predictive modeling, classification, regression, clustering, and natural language processing (NLP). Conduct statistical analysis to uncover trends, patterns, and actionable insights from large datasets. Work with senior data scientists and business stakeholders to understand project goals and contribute to data-driven solutions. Support the design and maintenance of data pipelines for data preprocessing, model training, evaluation, and basic deployment. Collaborate with software and data engineering teams to ensure smooth integration of models into production environments. Create dashboards, visualizations, and reports to communicate findings clearly to business users. Contribute to codebase quality and documentation, following best practices for reproducibility and scalability. Keep abreast of industry trends in machine learning and data science tools, and share relevant learnings with the team. Participate in model validation, tuning, and performance monitoring to improve model accuracy and efficiency. Qualifications & skills required 3 - 6 years of experience in data science, machine learning, or a related field, with a strong portfolio of projects. Advanced knowledge of machine learning algorithms (e.g., random forests, gradient boosting, deep learning) and statistical methods. Proficiency in programming languages such as Python, R, and SQL. Hands-on experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, and XGBoost.\ Strong experience working with large datasets, data cleaning, and preprocessing. Solid understanding of data visualization tools like Tableau, Power BI, or Matplotlib/Seaborn. Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, GCP, Azure) is a plus. Strong problem-solving skills and the ability to think critically about data and its implications for business strategy. Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders. Experience in mentoring junior data scientists and leading data science projects is highly preferred. Be a part of Junglee Games to: Value Customers & Data - Prioritize customers, use data-driven decisions, master KPIs, and leverage ideation and A/B testing to drive impactful outcomes. Inspire Extreme Ownership - We embrace ownership, collaborate effectively, and take pride in every detail to ensure every game becomes a smashing success. Lead with Love - We reject micromanagement and fear, fostering open dialogue, mutual growth, and a fearless yet responsible work ethic. Embrace change - Change drives progress and our strength lies in adapting swiftly and recognizing when to evolve to stay ahead. Play the Big Game - We think big, challenge norms, and innovate boldly, driving impactful results through fresh ideas and inventive problem-solving. Avail a comprehensive benefits package that includes paid gift coupons, fitness plans, gadget allowances, fuel costs, family healthcare, and much more. Know more about us Explore the world of Junglee Games through our website, www.jungleegames.com. Get a glimpse of what Life at Junglee Games looks like on LinkedIn. Here is a quick snippet of the Junglee Games Offsite 24 Liked what you saw so far? Be A Junglee

Our Tech Stack: Java, Spring, Rest API, Microservices, Kafka, Spark, NodeJS, AWS, Kubernetes, Terraform, AngularJS What you ll do Identify $ opportunities - think big picture, work with product, tech and customer-facing teams to identify the largest customer problems that can be solved using ML. Build business cases through a combination of market research and internal analytics Stakeholder relationships and strong communication - work closely with a wide variety of stakeholders to build cohesive plans and execute them. Influence senior leadership through a data-driven approach, including but not limited to market research, customer case studies and pilots/experimentation. Technical expertise, simplify complexity - build end to end ML models, be it classification/ unsupervised/ LLMs using a combination of structured and unstructured data. Work with upstream data engineering and software engineering teams to procure, process and transform data into meaningful features. Focus particularly on the data engineering aspect of the model building lifecycle. Always work backwards from the customer, to identify the simplest feasible solutions that can add maximum value. End to end ownership, delivering results - Take models into production and maintain them through effective ML engineering, demonstrate tangible business value, and deliver solutions rather than products. Qualifications- 5+ years of experience in the data science/machine learning domain, preferably with hands-on end-to-end model building experience Strong data engineering background, with ETL experience, building and maintaining pipelines, data modeling, data warehousing concepts, and familiarity with Big Data techniques Curious mind to learn, explore and identify biggest customer opportunities Build strong relationships across both technical and business/product teams, earn trust with leadership Driven towards forming opinions and conclusions through data and experimentation, rather than anecdotes and hearsay Willingness to dive deep into the tech stack as well as hands-on coding Experience in building end to end ML models, across the ML lifecycle Strong communication and leadership presence Technical skills- hands on with scripting required, with knowledge or willingness to learn tools/softwares. Knowledge of R, SQL, Python, Statistical modeling, experience with AWS/Azure/GCP ML suite Experience in the following domains/industries preferred- SaaS, ecommerce, pricing or payments Bachelors/Masters in a technical or natural sciences domain from a top university