Machine learning and GEN AI Data Scientist
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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 bank, mid-level ML/GenAI role, metro location and popular data-scientist title drive high competition.
Banking domain experience and model governance increase domain specificity, though ML skills remain transferable.
Explicit years and strong ML/LLM, PySpark, and model governance requirements enforce strict shortlisting.
Job Description
Structured overview of role & requirementsAbout This Role
Lead analytic projects for North America Consumer Bank focusing on new customer acquisition, retention, product development, pricing, and digital journey.
Develop, validate, implement, and govern predictive models using machine learning, deep learning, and generative AI (e.g., LLMs) on large complex datasets.
Collaborate with stakeholders and governance teams to ensure model compliance and risk management aligned with Citi standards.
Minimum Requirements
Bachelor’s degree with 3 years experience in data analytics, or Master’s degree with 2 years, or PhD.
Proficient in Python/PySpark/R programming and strong SQL skills.
Experience (2-4 years) in machine learning, statistical modeling, and familiarity with deep learning techniques.
Work Experience Required: 2-4 years in relevant analytic/data science roles with exposure to large datasets and model deployment.
Ideal Candidate Profile
Demonstrated ability to translate complex business problems into analytic modeling solutions involving machine learning, deep learning, and generative AI.
Experienced in managing multiple complex analytic projects and working cross-functionally with business and governance teams in a regulated banking environment.
Strong expertise in retail banking/credit card domain or similar, with knowledge of model governance and risk controls.