Lead AI/ML Data Scientist- Vice president at Citi
Chennai, TN
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Jul 28, 2026
Chennai, TN
Jul 29, 2026
What this job asks for AI summary
A senior individual-contributor data science role at Citi focused on building and deploying AI/ML models — including agentic and generative AI solutions — to power enterprise-scale financial data reconciliation across global Capital Markets operations. The position owns the full model development lifecycle from architecture through production, working closely with engineering and business teams. It suits an experienced ML practitioner with deep Python/big-data skills and hands-on LLM/agent-framework experience in a financial-services context.
Senior level · 10+ years · Full-time
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $122,874 (middle half $87,544–$162,374).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 29, 2026. It is a model, not a headcount.
Why we read it this way (6)
No work location is specified in the posting — the CBSA and state fields have been left blank. The role is listed under Citi's global operations context but no city or country is named.
The title 'Lead AI/ML Data Scientist' carries no standard seniority level word; advertised seniority is set to Unspecified. The 10+ years requirement and end-to-end ownership scope support a Senior classification.
The degree requirement lists Bachelor's or Master's as options with no hard minimum stated and no 'or equivalent experience' clause, but because both levels are offered as alternatives and neither is a strict floor, degree requirement is treated as None.
AWS SageMaker, Azure ML, and Google Vertex AI are explicitly labeled 'beneficial' in the posting and are grouped as interchangeable cloud ML platform options.
The 'Agent Development Kit (ADK)' listed under required Agentic AI tools is a less-established product; it has been omitted as a standalone skill because it lacks a canonical, widely-recognized name, but LangGraph and LangChain — the other named agent frameworks — are captured as required.
Statistical modeling techniques (GLM, NLP/LDA, sentiment analysis) appear under the 'Beneficial Skills' section and are represented through the preferred ML-library skills rather than as separate methodology entries, since the posting names no distinct tool for them beyond what is already captured.
Read the full posting
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