Role Overview:

We are looking for a Data Scientist with strong experience in data analytics, SQL, Databricks, and Data Analyst - With practical exposure to Generative AI and Agentic AI solutions.

The candidate will work closely with business stakeholders, Data Engineers, Data Scientists, and AI/technical teams to understand business requirements, analyze and validate data, and support data and AI solution delivery.

Key Responsibilities:

- Analyze business requirements and translate them into clear functional and data requirements.

- Perform hands-on data analysis using SQL and Databricks, including data validation, profiling, and troubleshooting.

- Work with Databricks notebooks, tables, queries, and analytical datasets.

- Support data modeling and identify relevant data sources for analytics and AI use cases.

- Work with data governance concepts such as Unity Catalog, metadata, lineage, permissions, and trusted datasets.

- Collaborate with Data Scientists, Data Engineers, and AI Engineers on Data Science, GenAI, and Agentic AI use cases.

- Understand and work with concepts such as LLMs, RAG, embeddings, vector search, prompt engineering, AI agents, tool/function calling, APIs, and agent workflows.

- Understand how enterprise data is retrieved, validated, governed, and consumed by AI solutions.

- Support UAT and solution validation for data, analytics, and AI solutions.

- Validate AI outputs for accuracy, relevance, grounding, and potential data issues.

- Identify data quality issues and help troubleshoot discrepancies in analytical or AI outputs.

- Participate in Agile delivery activities including backlog refinement, sprint planning, requirements clarification, and defect management.

- Work effectively with both business and technical stakeholders.

Preferred candidate profile:

- 4 - 9 years of experience in Data Engineer and Data Scientist, Business/Data Analysis, or a related role.

- Strong hands-on SQL and data analysis skills.

- Experience working with Databricks or a similar modern data platform.

- Good understanding of data modeling, data quality, validation, and data relationships.

- Experience gathering and documenting business/functional requirements.

- Understanding of Data Science concepts and experience working with or alongside Data Science teams.

- Practical experience or strong working knowledge of Generative AI / LLM - based solutions.

- Exposure to Agentic AI / AI Agent solutions and an understanding of how they work with enterprise data.

- Understanding of RAG, embeddings, vector search, tool/function calling, APIs, and AI agent workflows.

- Experience with UAT, Agile methodologies, and stakeholder communication.