Senior Data Scientist

Overview

Design, develop and deliver advanced AI and Agentic AI solutions that address complex business challenges and enhance customer experiences, working as a senior technical contributor across Product, Engineering, Data and Business teams.

What you'll do

• Design, develop and deploy scalable AI, Machine Learning, Generative AI and Agentic AI solutions, including intelligent assistants, copilots, conversational systems and enterprise-grade AI products.
• Translate business requirements into scalable AI architectures and technical solutions, defining solution designs, integration strategies, technical specifications, data flows and implementation approaches, aligned with security, governance, reliability, maintainability and responsible AI standards.
• Develop, evaluate and optimize AI and machine learning models and platforms, establishing testing frameworks, performance metrics, monitoring, observability and production-readiness practices.
• Lead end-to-end delivery of AI initiatives, including development, deployment, operationalization, troubleshooting, continuous improvement, enterprise integrations and collaboration with engineering teams to build scalable data pipelines and AI workflows.
• Partner with Product Managers, Engineering teams and business stakeholders to define product capabilities, technical requirements, roadmaps and best practices, providing technical leadership and communicating complex concepts to technical and non-technical audiences.

What you'll need

• Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Engineering or a related field.
• 8+ years of experience in Data Science, Machine Learning, Artificial Intelligence or software development.
• Demonstrated experience delivering production-grade AI or machine learning solutions.
• Strong experience with Generative AI, Large Language Models and modern AI frameworks.
• Experience designing scalable enterprise applications and distributed systems.
• Proven track record of independently owning and delivering complex technical initiatives.
• Strong stakeholder management and cross-functional collaboration skills.
• Advanced expertise in Artificial Intelligence, Data Science, Machine Learning and Generative AI, including Agentic AI, Large Language Models (LLMs), Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG), Prompt Engineering, Statistical Modeling, Predictive Analytics, Quantitative Analysis, Data Mining, Data Analysis and Applied AI solution development.
• Strong hands-on experience with modern AI and data science frameworks and tools, including LangChain, LangGraph, Azure OpenAI, NoSQL, Azure Machine Learning, TensorFlow, MLflow, LlamaFactory, Unsloth, Scikit-Learn, Pandas, NumPy, Matplotlib, SpaCy, GPT models, Embeddings and Vector Search technologies.
• Proficiency in Python, SQL, API development, FastAPI, Flask, distributed systems, cloud-native application development, CI/CD practices, Git, Jupyter and modern software engineering practices for production-grade AI solutions.
• Experience designing, developing and deploying enterprise-scale solutions on Azure, Azure AI Services, Azure Machine Learning, Azure OpenAI, Cosmos DB/DynamoDB, cloud-based AI platforms and containerized environments.
• Strong understanding of data engineering and analytics, including data pipelines, data cleansing, wrangling, visualization, feature engineering, experiment design, model evaluation, data modelling, analytics, business insights and AI performance measurement methodologies.
• Expertise in building scalable Conversational AI, Intelligent Agents, Multi-Agent Systems, Knowledge Retrieval platforms, AI orchestration frameworks, enterprise integrations and production AI systems, including fine-tuning, reasoning, document understanding, summarization, classification and question-answering solutions.
• Experience applying advanced machine learning techniques including classification, clustering, recommendation systems, forecasting, ensemble learning, hyperparameter tuning, feature selection, embedding-based modelling, similarity search and model optimization.

Details

• Location: Pune, India (Smartworks).
• Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.
• Interviews must be completed without AI tools or external prompts, and virtual backgrounds must be removed; in-person interviews are part of the process.