346 Data Scientist Jobs

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

About the job : We are looking for a highly skilled Senior AI/ML Engineer with 5+ years of experience to join our team. The ideal candidate should have extensive expertise in machine learning, deep learning, and AI model development, along with a strong background in Python, NLP, computer vision, and cloud-based AI solutions. Key Responsibilities : - Design, develop, and deploy AI/ML models for real-world applications. - Work with NLP, deep learning, and traditional ML algorithms to solve complex business problems. - Develop end-to-end ML pipelines, including data preprocessing, feature engineering, model training, and deployment. - Optimize model performance using hyperparameter tuning and model evaluation techniques. - Implement AI-driven solutions using TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, Hugging Face, and similar frameworks. - Work with structured and unstructured data, performing data wrangling, transformation, and feature extraction. - Deploy models in cloud environments (AWS, Azure, or GCP) using SageMaker, Vertex AI, or Azure ML. - Collaborate with cross-functional teams to integrate AI models into production systems. - Ensure scalability, performance, and efficiency of AI/ML solutions. - Stay updated with emerging AI trends and technologies to drive innovation. Required Skills : - Strong experience in machine learning, deep learning, NLP, and AI model development. - Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and OpenAI GPT models. - Expertise in NLP techniques (Word2Vec, BERT, transformers, LLMs, text classification). - Hands-on experience with computer vision (CNNs, OpenCV, YOLO, custom object detection models). - Solid understanding of ML model deployment and MLOps (Docker, Kubernetes, CI/CD for ML models). - Experience in working with cloud platforms (AWS, Azure, GCP) for AI/ML model deployment. - Strong knowledge of SQL, NoSQL databases, and big data processing tools (PySpark, Databricks, Hadoop, Kafka, etc. - Familiarity with API development using Django, Flask, or FastAPI for AI solutions. - Strong problem-solving, analytical, and communication skills. Preferred Skills : - Experience with AI-powered chatbots and OpenAI API integration. - Exposure to LLMs (GPT, LLaMA, Falcon, etc.) for real-world applications. - Hands-on experience in generative AI models.

Job Summary : We are seeking a skilled Data Scientist with expertise in AI orchestration and embedded systems to support a sprint-based Agile implementation focused on integrating generative AI capabilities into enterprise platforms such as Slack, Looker, and Confluence. The ideal candidate will have hands-on experience with Gemini and a strong understanding of prompt engineering, vector databases, and orchestration infrastructure. Key Responsibilities : - Develop and deploy Slack-based AI assistants leveraging Gemini models. - Design and implement prompt templates tailored to enterprise data use cases (Looker and Confluence). - Establish and manage an embedding pipeline for Confluence documentation. - Build and maintain orchestration logic for prompt execution and data retrieval. - Set up API authentication and role-based access controls for integrated systems. - Connect and validate vector store operations (e.g., Pinecone, Weaviate, or Snowflake vector extension). - Contribute to documentation, internal walkthroughs, and user acceptance testing planning. - Participate in Agile ceremonies including daily standups and sprint demos. Required Qualifications : - Proven experience with Gemini and large language model deployment in production environments. - Proficiency in Python, orchestration tools, and prompt engineering techniques. - Familiarity with vector database technologies and embedding workflows. - Experience integrating APIs for data platforms such as Looker and Confluence. - Strong understanding of access control frameworks and enterprise-grade authentication. - Demonstrated success in Agile, sprint-based project environments. Preferred Qualifications : - Experience working with Slack app development and deployment. - Background in MLOps, LLMOps, or AI system orchestration at scale. - Excellent communication skills and ability to work in cross-functional teams.

About the job : We are looking for a highly skilled Senior AI/ML Engineer with 5+ years of experience to join our team. The ideal candidate should have extensive expertise in machine learning, deep learning, and AI model development, along with a strong background in Python, NLP, computer vision, and cloud-based AI solutions. Key Responsibilities : - Design, develop, and deploy AI/ML models for real-world applications. - Work with NLP, deep learning, and traditional ML algorithms to solve complex business problems. - Develop end-to-end ML pipelines, including data preprocessing, feature engineering, model training, and deployment. - Optimize model performance using hyperparameter tuning and model evaluation techniques. - Implement AI-driven solutions using TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, Hugging Face, and similar frameworks. - Work with structured and unstructured data, performing data wrangling, transformation, and feature extraction. - Deploy models in cloud environments (AWS, Azure, or GCP) using SageMaker, Vertex AI, or Azure ML. - Collaborate with cross-functional teams to integrate AI models into production systems. - Ensure scalability, performance, and efficiency of AI/ML solutions. - Stay updated with emerging AI trends and technologies to drive innovation. Required Skills : - Strong experience in machine learning, deep learning, NLP, and AI model development. - Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and OpenAI GPT models. - Expertise in NLP techniques (Word2Vec, BERT, transformers, LLMs, text classification). - Hands-on experience with computer vision (CNNs, OpenCV, YOLO, custom object detection models). - Solid understanding of ML model deployment and MLOps (Docker, Kubernetes, CI/CD for ML models). - Experience in working with cloud platforms (AWS, Azure, GCP) for AI/ML model deployment. - Strong knowledge of SQL, NoSQL databases, and big data processing tools (PySpark, Databricks, Hadoop, Kafka, etc. - Familiarity with API development using Django, Flask, or FastAPI for AI solutions. - Strong problem-solving, analytical, and communication skills. Preferred Skills : - Experience with AI-powered chatbots and OpenAI API integration. - Exposure to LLMs (GPT, LLaMA, Falcon, etc.) for real-world applications. - Hands-on experience in generative AI models.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Job Summary : We are seeking a skilled Data Scientist with expertise in AI orchestration and embedded systems to support a sprint-based Agile implementation focused on integrating generative AI capabilities into enterprise platforms such as Slack, Looker, and Confluence. The ideal candidate will have hands-on experience with Gemini and a strong understanding of prompt engineering, vector databases, and orchestration infrastructure. Key Responsibilities : - Develop and deploy Slack-based AI assistants leveraging Gemini models. - Design and implement prompt templates tailored to enterprise data use cases (Looker and Confluence). - Establish and manage an embedding pipeline for Confluence documentation. - Build and maintain orchestration logic for prompt execution and data retrieval. - Set up API authentication and role-based access controls for integrated systems. - Connect and validate vector store operations (e.g., Pinecone, Weaviate, or Snowflake vector extension). - Contribute to documentation, internal walkthroughs, and user acceptance testing planning. - Participate in Agile ceremonies including daily standups and sprint demos. Required Qualifications : - Proven experience with Gemini and large language model deployment in production environments. - Proficiency in Python, orchestration tools, and prompt engineering techniques. - Familiarity with vector database technologies and embedding workflows. - Experience integrating APIs for data platforms such as Looker and Confluence. - Strong understanding of access control frameworks and enterprise-grade authentication. - Demonstrated success in Agile, sprint-based project environments. Preferred Qualifications : - Experience working with Slack app development and deployment. - Background in MLOps, LLMOps, or AI system orchestration at scale. - Excellent communication skills and ability to work in cross-functional teams.

One of the Healthcare AI Product Start up based out of Hyderabad is looking out for a AI Architect. If you are looking for a challenging environment and would like to be a part of building AI products, let us connect and discuss. Position: AI Architect Experience: 5+ yrs Qualification: B.Tech / B.E from Tier 1 Academic Institutions Job Type: Permanent & WFO Job Location: Hyderabad Position Overview We are seeking an experienced AI Architect to lead the design, development, and deployment of large-scale AI solutions. The ideal candidate will bridge the gap between business requirements and technical implementation, with deep expertise in generative AI and modern MLOps practices. Key Responsibilities: AI Solution Design & Implementation: • Architect end-to-end AI systems leveraging large language models and generative AI technologies • Design scalable, production-ready AI applications that meet business objectives and performance requirements • Evaluate and integrate LLM APIs from leading providers (OpenAI, Anthropic Claude, Google Gemini, etc.) • Establish best practices for prompt engineering, model selection, and AI system optimization Model Development & Fine-tuning: • Fine-tune open-source models (Llama, Mistral, etc.) for specific business use cases • Implement custom training pipelines and evaluation frameworks • Optimize model performance, latency, and cost for production environments • Stay current with latest model architectures and fine-tuning techniques Infrastructure & Deployment: • Deploy and manage AI models at enterprise scale using containerization (Docker) and orchestration (Kubernetes) • Build robust, scalable APIs using FastAPI and similar frameworks • Design and implement MLOps pipelines for model versioning, monitoring, and continuous deployment • Ensure high availability, security, and performance of AI systems in production Business & Technical Leadership: • Collaborate with stakeholders to understand business problems and translate them into technical requirements • Provide technical guidance and mentorship to development teams • Conduct feasibility assessments and technical due diligence for AI initiatives • Create technical documentation, architectural diagrams, and implementation roadmaps Required Qualifications: Experience • 5+ years of experience in machine learning engineering or data science • 1+ years of hands-on experience building, deploying, and managing generative AI models in production • Proven track record of delivering large-scale ML solutions Technical Skills: • Expert-level proficiency with LLM APIs (OpenAI, Claude, Gemini, etc.) • Hands-on experience fine-tuning transformer models (Llama, Mistral, etc.) • Strong proficiency in FastAPI, Docker, and Kubernetes • Experience with ML frameworks (PyTorch, TensorFlow, Hugging Face Transformers) • Proficiency in Python and modern software development practices • Experience with cloud platforms (AWS, GCP, or Azure) and their AI/ML services Core Competencies: • Strong understanding of transformer architectures, attention mechanisms, and modern NLP techniques • Experience with MLOps tools and practices (model versioning, monitoring, CI/CD) • Ability to translate complex business requirements into technical solutions • Strong problem-solving skills and architectural thinking Preferred Qualifications: • Experience with vector databases and retrieval-augmented generation (RAG) systems • Knowledge of distributed training and model parallelization techniques • Experience with model quantization and optimization for edge deployment • Familiarity with AI safety, alignment, and responsible AI practices • Experience in specific domains (finance, healthcare, legal, etc.) • Advanced degree in Computer Science, AI/ML, or related field Please Note: We are looking out for candidates who shorter notice period.

What we do : Our game-changing AI solutions revolutionize what people and businesses can achieve. Ara inference processors combined with our SDK deliver unrivaled deep learning performance at the edge to accelerate and optimize real-time decision making where every millisecond is critical, and power efficiency is a must. solutions embed high-performance AI into edge devices to create a smarter, safer, and more enjoyable world. Edge AI is on the brink of a boom, and looking forward to playing a significant role in it. This is what you are responsible for : - Will be part of a highly talented global team developing neural network systems. - Will have the opportunity to develop the application and system software for a cutting-edge AI silicon. - Member of a software engineering team, you will design and implement compilers, translators for AI computing system - Work closely with ASIC and hardware teams, propose architectural features and develop software for the system and build the highest perf/watt system Necessary Qualifications : - Excellent knowledge of Python/C/C++, data structures and algorithms. - Experience in neural network frameworks like TensorFlow, ONNX, Caffe, PyTorch etc. is a plus - BTech/MTech with 4+ years of experience in software development

Job Position :Principal Data Scientist / Sr Data Scientists /Data Scientist / Jr. Data Scientist / Data Science Intern / Machine Learning Engineer-Global Tech AI Health Startup. Joining : Immediately. Job Location : Delhi NCR, India.Global HQ, Benovymed Global Technology Development and Innovation Center & Benovymed Global R and D, and AI Health Innovation Center in Delhi NCR. Job Role Responsibility Description :We are looking for passionate, Strong experience with an entrepreneur mindset to join us as Hardcore Full Stack Data Scientist end-to-end single-handed multi-hat role who is already working in applied AI in ML, deep Learning, ANN, and CNN platform specifically working as single-handed doers or in a small Data Science Team with full end to end ownership of Data Science work commitment delivery as Data Scientist working in any reputed AI Data Science is driven Tech startup preferably in Healthcare.Required Skillsets :- Needs to have statistical, mathematical, and predictive modeling as well as business strategy skills to build the algorithms necessary to ask the right questions and find the right answers.- Need to be able to communicate their findings, orally and visually.- Need to understand how the products are developed and even more important, as big data touches the privacy of consumers, they need to have a set of ethical responsibilities.-- Need to have a natural desire to go beneath the surface of a problem.- Confident and self-secure as they more often than not will have to deal with situations where there is a lot of unknown.- Good knowledge & experience in Artificial Neural Network ( ANN ), AI conversational Chatbot & Needs to be able to write the required Algorithm and coding programming.- Preferably in different programming languages such as Python, Tensor Flow, Keras, AWS (ML and DL), Numpy, and Pytorch.In addition the need to be familiar with disciplines as follows :- Natural Language Processing, Machine learning, Conceptual modeling, Statistical analysis, Predictive Modeling, and Hypothesis testing.Data scientists should have at least some of the following capabilities :- Cleaning data, formatting data, Having the ability to query databases & perform statistical analysis, building AI Data Modelling, validating the AI Model, and deployment.- Being able to develop or program databases.- Having a good understanding of design & architecture principles. Qualification : B.Tech / M.Tech in CSE / Electrical / Electronics & Communication/ Maths & Computing /Statistics /BioTech/BioStat / Clinical Engineering in Data Science / Machine Learning from Top-rated Tech University / Top rated IIT /IIIT. Mandatory Requirement :Experience :- Post last qualification of at least 0 to 7 Years of strong experience exclusive in real Industry Projects in applied AI ML & Deep Learning Data Science in an early-stage AI Health startup at the role and designation as a single-handed full-stack Principal Data Scientist / Sr. Data Scientist.- Hardcore in ANN /Deep Learning /Machine Learning/NLP with at least 2-20 good Applied AI-oriented Applied Research Projects & applications with hardcore experience working on ANN, CNN, RNN, and deep learning in Digital Health startups to solve specific complex problems. CTC :- Best Package in Industry.- Terms & Conditions Apply as per our organization.- To deserving eligible candidates only, the company Equity / ESOP may be given also as a part of a Package for a long-term career opportunity.- Apply with your CV with passport size photo, & current CTC, expected CTC, Notice Period, Project details & cover letter.

What will your day look like - Leading a dynamic team to deliver high impact risk solutions across credit risk (underwriting, exposure controls and line management). - Work with stakeholders across product management, data science, and engineering to build relationship with the partner teams and drive implementation of risk strategies - Manage challenging time constraints to ensure on-time delivery of projects. - Work closely with partner teams in identifying, evaluating, and recommending new data that helps in risk differentiation. - Analyze loss trends and simulate risk decisioning strategies that help optimize revenue, approval rates etc. - Work closely with data science team and recommends credit risk decisioning and model deployment strategy. - Build a risk scorecard that leverages both internal performance data and external performance data that will be leveraged for credit decisioning at both underwriting and account management reviews for existing customers. - Collates analysis and builds presentations that helps articulate the risk strategy for the leadership team. To Help Us Level Up, You Will Ideally Have : - Quantitative background in engineering, statistics, math, economics, business, or related disciplines. - 5+ years experience in analyzing data and using database query language (e. SQL) analysis and programming and developer tools such as Python, R, data bricks in a finance or analytics field. - 2+ years of experience in leading high performing team of analysts. - Experience in working with non-traditional data such as social media will be a big plus. - Prior model building experience is a plus but not critical. - Possesses an analytical mindset and strong problem-solving skills. - Attention to detail and ability to multitask. - Comfortable working in a fast-paced environment and dealing with ambiguity. - Possesses strong communication, interpersonal and presentation skills; and ability to engage and collaborate with multiple stakeholders across teams. - Extremely proactive communicator willing to raise flags when needed and keep team members informed of ongoing risk or fraud related activities.

Job Summary : We are seeking a skilled Data Scientist with expertise in AI orchestration and embedded systems to support a sprint-based Agile implementation focused on integrating generative AI capabilities into enterprise platforms such as Slack, Looker, and Confluence. The ideal candidate will have hands-on experience with Gemini and a strong understanding of prompt engineering, vector databases, and orchestration infrastructure. Key Responsibilities : - Develop and deploy Slack-based AI assistants leveraging Gemini models. - Design and implement prompt templates tailored to enterprise data use cases (Looker and Confluence). - Establish and manage an embedding pipeline for Confluence documentation. - Build and maintain orchestration logic for prompt execution and data retrieval. - Set up API authentication and role-based access controls for integrated systems. - Connect and validate vector store operations (e.g., Pinecone, Weaviate, or Snowflake vector extension). - Contribute to documentation, internal walkthroughs, and user acceptance testing planning. - Participate in Agile ceremonies including daily standups and sprint demos. Required Qualifications : - Proven experience with Gemini and large language model deployment in production environments. - Proficiency in Python, orchestration tools, and prompt engineering techniques. - Familiarity with vector database technologies and embedding workflows. - Experience integrating APIs for data platforms such as Looker and Confluence. - Strong understanding of access control frameworks and enterprise-grade authentication. - Demonstrated success in Agile, sprint-based project environments. Preferred Qualifications : - Experience working with Slack app development and deployment. - Background in MLOps, LLMOps, or AI system orchestration at scale. - Excellent communication skills and ability to work in cross-functional teams.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Data Scientist Job title: Data Scientist Location: Noida(Work from Office) Shift: US Shift Design, build, and maintain robust and scalable applications using Python and advanced AI frameworks. Develop complex, multi-step workflows and autonomous systems using LLM Orchestrators like LangChain, LlamaIndex, or Semantic Kernel. Integrate AI models and agentic systems with our existing data pipelines, APIs, and infrastructure. Collaborate with product managers, data scientists, and software engineers to define requirements and deliver high-impact AI features. Establish AI Development Standards: Design and implement industry best practices for building, testing, and deploying scalable AI Agents (RAG, Prompting, Chat Completion, Multi-agent, Fine-Tuning), particularly focusing on generative models and large language models (LLMs) using both proprietary and open-source frameworks. Stay Ahead of Industry Trends: Continuously research and adopt the latest advancements in AI, ML, and generative models to drive innovation and operational improvements. Engage in Cross-Team Collaboration: Partner with stakeholders across data science, engineering, operations, and business teams to align AI initiatives with broader organizational goals. Train and manage the inference of deep learning models (Bert/Roberta/XL-Net/T4REC) and locally hosted LLMs (Llama/Qwen/Mistral) Manage model training, serving and response times at scale by techniques like model quantisation, QAT (quantisation aware training), speculative decoding, flash attention etc Required Qualifications Bachelor's degree in Computer Science, AI, Engineering, or a related technical field. 2 - 5 years of professional software development experience with a strong proficiency in Python. Demonstrated hands-on experience working with LLMs (e.g., GPT series, Llama, Claude, Gemini) via APIs or open-source models. Proven experience building applications with an LLM Orchestrator framework (LangChain, LlamaIndex, etc.). Solid understanding of AI Agent architectures and concepts like ReAct (Reasoning and Acting). Strong analytical and problem-solving skills, with a passion for building intelligent systems. Preferred Qualifications Experience with cloud platforms like Azure, AWS, or GCP. Experience with MLOps practices and tools for deploying and monitoring models in production. Familiarity with vector databases (e.g., Pinecone, Weaviate, ChromaDB). Active contributions to open-source AI/ML projects

What will your day look like - Leading a dynamic team to deliver high impact risk solutions across credit risk (underwriting, exposure controls and line management). - Work with stakeholders across product management, data science, and engineering to build relationship with the partner teams and drive implementation of risk strategies - Manage challenging time constraints to ensure on-time delivery of projects. - Work closely with partner teams in identifying, evaluating, and recommending new data that helps in risk differentiation. - Analyze loss trends and simulate risk decisioning strategies that help optimize revenue, approval rates etc. - Work closely with data science team and recommends credit risk decisioning and model deployment strategy. - Build a risk scorecard that leverages both internal performance data and external performance data that will be leveraged for credit decisioning at both underwriting and account management reviews for existing customers. - Collates analysis and builds presentations that helps articulate the risk strategy for the leadership team. To Help Us Level Up, You Will Ideally Have : - Quantitative background in engineering, statistics, math, economics, business, or related disciplines. - 5+ years experience in analyzing data and using database query language (e. SQL) analysis and programming and developer tools such as Python, R, data bricks in a finance or analytics field. - 2+ years of experience in leading high performing team of analysts. - Experience in working with non-traditional data such as social media will be a big plus. - Prior model building experience is a plus but not critical. - Possesses an analytical mindset and strong problem-solving skills. - Attention to detail and ability to multitask. - Comfortable working in a fast-paced environment and dealing with ambiguity. - Possesses strong communication, interpersonal and presentation skills; and ability to engage and collaborate with multiple stakeholders across teams. - Extremely proactive communicator willing to raise flags when needed and keep team members informed of ongoing risk or fraud related activities.

Role Data Scientist Manager Years of Experience –10+ years Purpose of Role In this role, The Candidate should be highly analytical with a knack for analysis, math, and statistics. Critical thinking and problem-solving skills are essential for interpreting data. To help our company analyze trends to make better decisions. Build propensity models, customer segmentations, uplift models, campaign response models, risk, and fraud detection models. Also, Integrate the models with the business processes and consuming systems via ML Ops processes. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to evaluate the effectiveness of different courses of action. Key Accountabilities Responsibilities will include but will not be restricted to: Create models as required by the business with a high degree of precision and recall. Model accuracy and stability are key accountabilities. Understand business priorities and align data science deliverables to ensure the business receives the intelligence and modeling inputs to drive decisions. Work with stakeholders throughout the organization to identify opportunities for using company data to drive business solutions. Undertake preprocessing of structured and unstructured data and analyze large amounts of information to discover trends and patterns. Assess the effectiveness and accuracy of new data sources and data gathering techniques. Coordinate with different functional teams to implement models and monitor outcomes. Recruit, train, develop and supervise Junior level employees. Develop processes and tools to monitor and analyze model performance and data accuracy. Technical Requirements (what) Proven experience of 8+ years as a Data Scientist. Post Graduate degree in Computer Science, Statistics, Engineering, Physics, Mathematics, Econometrics or MBA with a ML/DS focus. Knowledge of SQL and R or Python; familiarity with Scala & SPARK is an asset. Candidates with experience of working on AWS stack will be preferred, however this is not a compulsory requirement. Knowledge and experience in machine learning, optimization, statistical and data mining techniques- regression, simulation, clustering, decision trees, classification algos (bagging/boosting), neural networks. Desired Personal Qualities or Behavior Strong Analytical critical thinking skills and business acumen Strong commitment to professional development. Process Oriented and excellent time management skills. Ability to adapt to new situations and issues and to solve problems. Good organizational, communication, presentational and people skills - with the capability to communicate concisely and effectively equally well with fellow employees, non-technical colleagues and with members and/or customers alike. Role & responsibilities Preferred candidate profile Perks and benefits

Job Title : Data Scientist - AI Integration & Orchestration. Job Summary : We are seeking a skilled Data Scientist with expertise in AI orchestration and embedded systems to support a sprint-based Agile implementation focused on integrating generative AI capabilities into enterprise platforms such as Slack, Looker, and Confluence. The ideal candidate will have hands-on experience with Gemini and a strong understanding of prompt engineering, vector databases, and orchestration infrastructure. Key Responsibilities : - Develop and deploy Slack-based AI assistants leveraging Gemini models. - Design and implement prompt templates tailored to enterprise data use cases (Looker and Confluence). - Establish and manage an embedding pipeline for Confluence documentation. - Build and maintain orchestration logic for prompt execution and data retrieval. - Set up API authentication and role-based access controls for integrated systems. - Connect and validate vector store operations (e.g., Pinecone, Weaviate, or Snowflake vector extension). - Contribute to documentation, internal walkthroughs, and user acceptance testing planning. - Participate in Agile ceremonies including daily standups and sprint demos. Required Qualifications : - Proven experience with Gemini and large language model deployment in production environments. - Proficiency in Python, orchestration tools, and prompt engineering techniques. - Familiarity with vector database technologies and embedding workflows. - Experience integrating APIs for data platforms such as Looker and Confluence. - Strong understanding of access control frameworks and enterprise-grade authentication. - Demonstrated success in Agile, sprint-based project environments. Preferred Qualifications : - Experience working with Slack app development and deployment. - Background in MLOps, LLMOps, or AI system orchestration at scale. - Excellent communication skills and ability to work in cross-functional teams.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

About the job : We are looking for a highly skilled Senior AI/ML Engineer with 5+ years of experience to join our team. The ideal candidate should have extensive expertise in machine learning, deep learning, and AI model development, along with a strong background in Python, NLP, computer vision, and cloud-based AI solutions. Key Responsibilities : - Design, develop, and deploy AI/ML models for real-world applications. - Work with NLP, deep learning, and traditional ML algorithms to solve complex business problems. - Develop end-to-end ML pipelines, including data preprocessing, feature engineering, model training, and deployment. - Optimize model performance using hyperparameter tuning and model evaluation techniques. - Implement AI-driven solutions using TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, Hugging Face, and similar frameworks. - Work with structured and unstructured data, performing data wrangling, transformation, and feature extraction. - Deploy models in cloud environments (AWS, Azure, or GCP) using SageMaker, Vertex AI, or Azure ML. - Collaborate with cross-functional teams to integrate AI models into production systems. - Ensure scalability, performance, and efficiency of AI/ML solutions. - Stay updated with emerging AI trends and technologies to drive innovation. Required Skills : - Strong experience in machine learning, deep learning, NLP, and AI model development. - Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and OpenAI GPT models. - Expertise in NLP techniques (Word2Vec, BERT, transformers, LLMs, text classification). - Hands-on experience with computer vision (CNNs, OpenCV, YOLO, custom object detection models). - Solid understanding of ML model deployment and MLOps (Docker, Kubernetes, CI/CD for ML models). - Experience in working with cloud platforms (AWS, Azure, GCP) for AI/ML model deployment. - Strong knowledge of SQL, NoSQL databases, and big data processing tools (PySpark, Databricks, Hadoop, Kafka, etc. - Familiarity with API development using Django, Flask, or FastAPI for AI solutions. - Strong problem-solving, analytical, and communication skills. Preferred Skills : - Experience with AI-powered chatbots and OpenAI API integration. - Exposure to LLMs (GPT, LLaMA, Falcon, etc.) for real-world applications. - Hands-on experience in generative AI models.

Role Data Scientist Manager Years of Experience –10+ years Purpose of Role In this role, The Candidate should be highly analytical with a knack for analysis, math, and statistics. Critical thinking and problem-solving skills are essential for interpreting data. To help our company analyze trends to make better decisions. Build propensity models, customer segmentations, uplift models, campaign response models, risk, and fraud detection models. Also, Integrate the models with the business processes and consuming systems via ML Ops processes. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to evaluate the effectiveness of different courses of action. Key Accountabilities Responsibilities will include but will not be restricted to: Create models as required by the business with a high degree of precision and recall. Model accuracy and stability are key accountabilities. Understand business priorities and align data science deliverables to ensure the business receives the intelligence and modeling inputs to drive decisions. Work with stakeholders throughout the organization to identify opportunities for using company data to drive business solutions. Undertake preprocessing of structured and unstructured data and analyze large amounts of information to discover trends and patterns. Assess the effectiveness and accuracy of new data sources and data gathering techniques. Coordinate with different functional teams to implement models and monitor outcomes. Recruit, train, develop and supervise Junior level employees. Develop processes and tools to monitor and analyze model performance and data accuracy. Technical Requirements (what) Proven experience of 8+ years as a Data Scientist. Post Graduate degree in Computer Science, Statistics, Engineering, Physics, Mathematics, Econometrics or MBA with a ML/DS focus. Knowledge of SQL and R or Python; familiarity with Scala & SPARK is an asset. Candidates with experience of working on AWS stack will be preferred, however this is not a compulsory requirement. Knowledge and experience in machine learning, optimization, statistical and data mining techniques- regression, simulation, clustering, decision trees, classification algos (bagging/boosting), neural networks. Desired Personal Qualities or Behavior Strong Analytical critical thinking skills and business acumen Strong commitment to professional development. Process Oriented and excellent time management skills. Ability to adapt to new situations and issues and to solve problems. Good organizational, communication, presentational and people skills - with the capability to communicate concisely and effectively equally well with fellow employees, non-technical colleagues and with members and/or customers alike. Role & responsibilities Preferred candidate profile Perks and benefits

Role Data Scientist Manager Years of Experience –10+ years Purpose of Role In this role, The Candidate should be highly analytical with a knack for analysis, math, and statistics. Critical thinking and problem-solving skills are essential for interpreting data. To help our company analyze trends to make better decisions. Build propensity models, customer segmentations, uplift models, campaign response models, risk, and fraud detection models. Also, Integrate the models with the business processes and consuming systems via ML Ops processes. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to evaluate the effectiveness of different courses of action. Key Accountabilities Responsibilities will include but will not be restricted to: Create models as required by the business with a high degree of precision and recall. Model accuracy and stability are key accountabilities. Understand business priorities and align data science deliverables to ensure the business receives the intelligence and modeling inputs to drive decisions. Work with stakeholders throughout the organization to identify opportunities for using company data to drive business solutions. Undertake preprocessing of structured and unstructured data and analyze large amounts of information to discover trends and patterns. Assess the effectiveness and accuracy of new data sources and data gathering techniques. Coordinate with different functional teams to implement models and monitor outcomes. Recruit, train, develop and supervise Junior level employees. Develop processes and tools to monitor and analyze model performance and data accuracy. Technical Requirements (what) Proven experience of 8+ years as a Data Scientist. Post Graduate degree in Computer Science, Statistics, Engineering, Physics, Mathematics, Econometrics or MBA with a ML/DS focus. Knowledge of SQL and R or Python; familiarity with Scala & SPARK is an asset. Candidates with experience of working on AWS stack will be preferred, however this is not a compulsory requirement. Knowledge and experience in machine learning, optimization, statistical and data mining techniques- regression, simulation, clustering, decision trees, classification algos (bagging/boosting), neural networks. Desired Personal Qualities or Behavior Strong Analytical critical thinking skills and business acumen Strong commitment to professional development. Process Oriented and excellent time management skills. Ability to adapt to new situations and issues and to solve problems. Good organizational, communication, presentational and people skills - with the capability to communicate concisely and effectively equally well with fellow employees, non-technical colleagues and with members and/or customers alike. Role & responsibilities Preferred candidate profile Perks and benefits

Job Role Responsibility Description : We are looking for passionate, Strong experience with an entrepreneur mindset to join us as Hardcore Full Stack Data Scientist end-to-end single-handed multi-hat role who is already working in applied AI in ML, deep Learning, ANN, and CNN platform specifically working as single-handed doers or in a small Data Science Team with full end to end ownership of Data Science work commitment delivery as Data Scientist working in any reputed AI Data Science is driven Tech startup preferably in Healthcare. Required Skillsets : - Needs to have statistical, mathematical, and predictive modeling as well as business strategy skills to build the algorithms necessary to ask the right questions and find the right answers. - Need to be able to communicate their findings, orally and visually. - Need to understand how the products are developed and even more important, as big data touches the privacy of consumers, they need to have a set of ethical responsibilities.- - Need to have a natural desire to go beneath the surface of a problem. - Confident and self-secure as they more often than not will have to deal with situations where there is a lot of unknown. - Good knowledge & experience in Artificial Neural Network ( ANN ), AI conversational Chatbot & Needs to be able to write the required Algorithm and coding programming. - Preferably in different programming languages such as Python, Tensor Flow, Keras, AWS (ML and DL), Numpy, and Pytorch. In addition the need to be familiar with disciplines as follows : - Natural Language Processing, Machine learning, Conceptual modeling, Statistical analysis, Predictive Modeling, and Hypothesis testing. Data scientists should have at least some of the following capabilities : - Cleaning data, formatting data, Having the ability to query databases & perform statistical analysis, building AI Data Modelling, validating the AI Model, and deployment. - Being able to develop or program databases. - Having a good understanding of design & architecture principles. Qualification : B.Tech / M.Tech in CSE / Electrical / Electronics & Communication/ Maths & Computing /Statistics /BioTech/BioStat / Clinical Engineering in Data Science / Machine Learning from Top-rated Tech University / Top rated IIT /IIIT. Mandatory Requirement : Experience : - Post last qualification of at least 0 to 7 Years of strong experience exclusive in real Industry Projects in applied AI ML & Deep Learning Data Science in an early-stage AI Health startup at the role and designation as a single-handed full-stack Principal Data Scientist / Sr. Data Scientist. - Hardcore in ANN /Deep Learning /Machine Learning/NLP with at least 2-20 good Applied AI-oriented Applied Research Projects & applications with hardcore experience working on ANN, CNN, RNN, and deep learning in Digital Health startups to solve specific complex problems.

We are looking for Data Scientist with AI specialization as mentioned in JD. Python is at core for this requirement with emphasis on Azure AI services including AI frameworks mentioned in JD As an Azure Data ScientistAI Engineer for Agent Development you will be at the forefront of our AI initiatives transforming complex business problems into sophisticated agentbased solutions You will work closely with crossfunctional teams to understand requirements design agent architectures implement and optimize agentic behaviors and ensure seamless integration and deployment on Azure Key Responsibilities Agent System Design Architecture Design develop and implement endtoend agentbased AI systems using frameworks such as Autogen Langgraph and CrewAI This includes defining agent roles communication protocols and task orchestration Azure Platform Expertise Leverage a wide range of Azure services including Azure Machine Learning Azure OpenAI Service Azure Databricks Azure Functions and other relevant data and AI services for building training deploying and managing agent solutions Large Language Model LLM Integration Integrate and finetune LLMs eg GPTx models via Azure OpenAI within agentic workflows focusing on prompt engineering context management and optimizing LLM interactions for specific tasks Data Preparation Feature Engineering Work with diverse datasets on Azure performing data cleaning transformation and feature engineering to prepare data for agent consumption and to enhance agent performance Workflow Orchestration Develop and manage complex stateful agent workflows using Langgraph for intricate decisionmaking processes loops and conditional logic MultiAgent Collaboration Implement and optimize multiagent collaboration strategies using Autogen to enable agents to converse delegate tasks and collectively solve problems CrewAI Implementation Utilize CrewAI to define and orchestrate collaborative agent crews with distinct roles tools and shared objectives for streamlined task execution Tool Development Develop custom tools and integrations for agents to interact with external APIs databases and other systems extending their capabilities Deployment MLOps Operationalize agent solutions on Azure including containerization Docker KubernetesAKS setting up CICD pipelines monitoring agent performance and implementing robust MLOps practices for continuous improvement Performance Optimization Scalability Identify and implement strategies to optimize the performance efficiency and scalability of agent systems on Azure Research Innovation Stay uptodate with the latest advancements in AI LLMs and agentic AI frameworks researching and evaluating new technologies for potential application Collaboration Communication Work effectively with data engineers software engineers product managers and business stakeholders to translate requirements into technical solutions and communicate complex concepts clearly Responsible AI Ensure the ethical development and deployment of AI agents addressing bias fairness transparency and security concerns Required Skills and Qualifications Bachelors or Masters degree in Computer Science Data Science Artificial Intelligence or a related quantitative field If PhD will be good Proven experience 12yrs as a Data Scientist or AI Engineer with a strong focus on building and deploying machine learning or AI solutions Deep expertise in Azure cloud services specifically Azure Machine Learning Azure OpenAI Service Azure Databricks Azure Functions Azure Data Lake Storage etc Strong programming skills in Python Python PyTorch TensorFlow Scikitlearn Handson experience with agent orchestration frameworks Autogen Experience in building multiagent conversational systems and enabling dynamic collaboration Langgraph Proficiency in designing and implementing stateful graphbased agent workflows with complex logic CrewAI Experience in orchestrating roleplaying autonomous AI agents for collaborative task execution Solid understanding of Large Language Models LLMs prompt engineering and RAG Retrieval Augmented Generation techniques Experience with MLOps practices including CICD model monitoring and version control Git Familiarity with containerization technologies Docker Kubernetes Strong analytical and problemsolving skills with the ability to translate business requirements into technical solutions Excellent communication and collaboration skills

Responsibilities : - Transform raw and unstructured data into structured, actionable formats for analysis and reporting. - Write, optimize, and maintain SQL queries and stored procedures to ensure efficient data retrieval and processing. - Design and implement complex SQL queries, including Common Table Expressions (CTEs), window functions, recursive queries, dynamic pivoting and joins, to extract actionable insights from large datasets efficiently. - Design, develop, and maintain databases and data pipelines to support analytics and reporting needs. - Perform data engineering tasks, including data ingestion, cleaning, and preprocessing. - Conduct exploratory data analysis (EDA) to uncover trends, patterns, and insights. - Develop and implement machine learning (ML) models and natural language processing (NLP) solutions to solve business challenges. - Build and monitor key performance indicators (KPIs) for dashboards and reporting tools. - Create wireframes and collaborate with stakeholders to design intuitive data visualizations and dashboards. - Ensure data integrity and perform quality checks to maintain high standards of accuracy and reliability. - Collaborate with cross-functional teams to align data initiatives with business goals. - Manage data science projects from ideation to deployment, ensuring timely delivery and measurable impact. - Communicate findings and insights effectively through presentations and reports to technical and non-technical audiences/ stakeholders. - Utilize statistical modelling and data mining techniques to drive decision-making and strategy. Must-Have Skills : - Proficiency in SQL and Python/R for data manipulation and analysis. - Experience with Machine Learning (ML) and NLP techniques. - Strong understanding of EDA and statistical modelling. - Hands-on experience with Google Cloud Platform (GCP) and Vertex AI. - Excellent communication and presentation skills. - Solid grasp of data engineering principles, including ETL processes. Good-to-Have Skills : - Knowledge of data mining techniques. - Knowledge of generative AI tools and frameworks for tasks such as synthetic data generation and data augmentation. - Familiarity with dashboard wireframe creation tools and methods. - Ability to build or derive KPIs for visualization dashboards. - Expertise in Excel for advanced calculations and analysis. - Background in project management, including Agile or similar methodologies. - Experience in cross-functional team collaboration. - Hands-on experience fine-tuning or deploying pre-trained Gen AI models (e.g., Hugging Face Transformers, OpenAI APIs)

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.