Machine learning and GEN AI Data Scientist
Citi (company site, opens in a new tab)3–5 yrsGurugramOn-siteDirect career pageEst. 16–28 LPA
Posted 12h ago
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Reach people at Citi
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Citi you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Own multiple complex analytics projects involving large datasets using Python, PySpark, SQL, and Hive to build and deploy deep learning and generative AI solutions across various business portfolios.
- Design, fine-tune and implement large language models (LLMs) and generative AI applications using prompt engineering, RAG, and model governance techniques to support functions like marketing, risk, digital, and AML.
- Collaborate with business and governance teams to ensure models comply with Citi standards and regulations, drive economic value, and impact areas including new customer acquisition, retention, product development, and digital journey optimization.
Minimum Requirements
- Bachelor's degree with 3 years experience in data analytics, or Master's degree with 2 years experience, or PhD in relevant quantitative fields (Economics, Statistics, Mathematics, IT, Engineering).
- 2-5 years hands-on experience in machine learning, statistical modeling, and deep learning techniques, including experience with ML frameworks and model validation/maintenance in production.
- Strong programming skills with Python, PySpark, R, strong SQL experience, and ability to work with large complex datasets and data warehouses.
- Experience or knowledge in Credit Cards and Retail Banking preferred; strong statistical analysis background required.
Ideal Candidate Profile
- Proven capability in executing end-to-end AI/ML analytics projects with focus on generative AI and deep learning applications in financial services.
- Experienced in collaborating across multiple stakeholders, including compliance and governance teams, ensuring regulatory adherence and risk-aware model deployment.
- Strong domain expertise or interest in consumer banking and credit card analytics, with ability to convert business problems into modeling solutions that create economic value.