Senior Data Scientist - R01559352
About The Position
About Brillio: Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction. Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work® certification year after year. Senior Data Scientist Primary Skills Problem Formulation (Business problem to Data Science Problem), OKR Validation against statistical measures, Data Wrangling, Data Storytelling & Insight Generation, Problem Solving, Excel VBA, Data Curiosity, Technical Decision Making (How many iterations to go for vs when to stop iterating), Communication & Articulation: Vocal & Written, Business Acumen (Consume new domains quickly to learn through data), Design Thinking, Data Literacy Specialization Data Science Foundation: Data Scientist Job requirements Senior Data Scientist Key Skills Strong proficiency in Python and SQL, ML, and GenAI pipelines Hands-on experience with GenAI / LLM-based systems (RAG, Fine Tuning, agents) Solid understanding of retrieval-augmented generation (RAG) architectures and vector databases Experience applying ML algorithms (classification, regression, ensembles) on structured BFSI data BFSI domain knowledge (banking, risk, fraud, compliance etc) Experience with LLM platforms and APIs (OpenAI, Azure OpenAI, AWS Bedrock, etc.) Ability to design prompt strategies, guardrails, and evaluation metrics for GenAI systems Understanding of data lineage, metadata, and traceability concepts in enterprise systems Experience working on cloud-based data and AI platforms (AWS/Azure) Strong problem-solving, communication, and stakeholder-facing skills in client environments Scope of Work / Responsibilities Design and build end-to-end GenAI solutions for BFSI use cases (RAG, agents) Develop and optimize data ingestion, chunking, embedding, and retrieval pipelines Integrate domain and regulatory requirements into AI/ML solution design Contribute to or implement data lineage-aware pipelines for traceability and audit readiness Develop production-quality Python code and reusable AI/ML components Perform model, prompt, and retrieval evaluation, monitoring, and performance tuning Support client interactions, solution walkthroughs, and technical documentation Mentor junior data scientists and act as a technical owner for assigned AI/GenAI modules
Requirements
- Problem Formulation (Business problem to Data Science Problem)
- OKR Validation against statistical measures
- Data Wrangling
- Data Storytelling & Insight Generation
- Problem Solving
- Excel VBA
- Data Curiosity
- Technical Decision Making (How many iterations to go for vs when to stop iterating)
- Communication & Articulation: Vocal & Written
- Business Acumen (Consume new domains quickly to learn through data)
- Design Thinking
- Data Literacy
- Strong proficiency in Python and SQL, ML, and GenAI pipelines
- Hands-on experience with GenAI / LLM-based systems (RAG, Fine Tuning, agents)
- Solid understanding of retrieval-augmented generation (RAG) architectures and vector databases
- Experience applying ML algorithms (classification, regression, ensembles) on structured BFSI data
- BFSI domain knowledge (banking, risk, fraud, compliance etc)
- Experience with LLM platforms and APIs (OpenAI, Azure OpenAI, AWS Bedrock, etc.)
- Ability to design prompt strategies, guardrails, and evaluation metrics for GenAI systems
- Understanding of data lineage, metadata, and traceability concepts in enterprise systems
- Experience working on cloud-based data and AI platforms (AWS/Azure)
- Strong problem-solving, communication, and stakeholder-facing skills in client environments
Responsibilities
- Design and build end-to-end GenAI solutions for BFSI use cases (RAG, agents)
- Develop and optimize data ingestion, chunking, embedding, and retrieval pipelines
- Integrate domain and regulatory requirements into AI/ML solution design
- Contribute to or implement data lineage-aware pipelines for traceability and audit readiness
- Develop production-quality Python code and reusable AI/ML components
- Perform model, prompt, and retrieval evaluation, monitoring, and performance tuning
- Support client interactions, solution walkthroughs, and technical documentation
- Mentor junior data scientists and act as a technical owner for assigned AI/GenAI modules
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
5,001-10,000 employees
