Senior Data Scientist

wk; India; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

wk is seeking a Senior Data Scientist to design, develop, and deliver scalable AI and Agentic AI solutions that address complex business challenges and enhance customer experiences.

The role requires deep expertise in ML, Generative AI, LLMs, NLP, and distributed systems, with a track record of delivering production-grade AI platforms and leading large initiatives from concept to deployment.

Qualifications

• Master's degree or higher in a related field.
• 8+ years of experience in data science, ML, AI, or software development.
• Proven track record delivering production-grade AI solutions.
• Strong experience with Generative AI, LLMs, and modern AI frameworks.
• Experience designing scalable enterprise applications and distributed systems.
• Independent ownership of complex technical initiatives.
• Strong stakeholder management and cross-functional collaboration.

Responsibilities

• Design, develop, and deploy scalable AI, ML, Generative AI, and Agentic AI solutions.
• Translate business requirements into scalable AI architectures and designs.
• Develop, evaluate, and optimize AI models and platforms with production-readiness practices.
• Lead end-to-end delivery of AI initiatives and enterprise integrations.
• Partner with product, engineering, and business teams to define roadmaps and best practices.

Skills

Advanced AI & ML

Generative AI

Large Language Models (LLMs)

NLP & Knowledge Retrieval

Python

SQL

Distributed Systems

Education

Master's degree in CS/AI/Data Science

Tools

LangChain

Azure OpenAI

TensorFlow

MLflow

Unit Testing & CI/CD

Job description

About the Role:

The Senior Data Scientist is responsible for designing, developing, and delivering advanced Artificial Intelligence and Agentic AI solutions that address complex business challenges and enhance customer experiences. This role combines expertise in Data Science, Machine Learning, Generative AI, and software architecture to deliver scalable, production-ready AI products and platforms. The position serves as a senior technical contributor who collaborates across Product, Engineering, Data, and Business teams to define solution strategies, drive implementation, and ensure successful delivery of AI-enabled capabilities. The role requires strong technical depth, business understanding, architectural thinking, and the ability to independently lead large and complex initiatives from concept through production deployment. This aligns with your demonstrated work on AI architecture, product specifications, performance engineering, and agent‑based solutions.

Key Responsibilities:

• 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 that solve complex business problems and deliver measurable value.
• Translate business requirements into scalable AI architectures and technical solutions by defining solution designs, integration strategies, technical specifications, data flows, and implementation approaches while ensuring alignment 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 to improve accuracy, scalability, efficiency, and business impact.
• Lead end‑to‑end delivery of AI initiatives by driving solution 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 while providing technical leadership, influencing architectural decisions, and effectively communicating complex concepts to technical and non‑technical audiences.

Required Qualifications:

• 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.

Technical 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/Dynamo DB, 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, recommenda