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Citi

Lead Data Scientist- Gen AI-ML- Vice president

Chennai · Staff/Principal

Older listing - lower visibility likelyVerified listingPosted 65d ago

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Skills required

45 listed
Retrieval-Augmented Generation (RAG)K-Means ClusteringNatural Language ProcessingWeights & BiasesMachine LearningAgentic AIData PreprocessingFinancial Data+37 more
Retrieval-Augmented Generation (RAG)K-Means ClusteringNatural Language ProcessingWeights & BiasesMachine Learning

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Job description

About the Team:

Citi is looking for a Lead Gen AI/ML- Data Scientist to join the Olympus Data Reconciliation and Engineering team, where you will shape the next generation of AI and machine learning capabilities powering enterprise-scale reconciliation across global processing hubs.

In this role, you will drive the full lifecycle of ML model development — from ideation and architecture through to deployment and adoption — delivering measurable impact across Capital Markets operations, risk, and finance. Your work will sit at the intersection of advanced data science and real-world financial systems, influencing outcomes at a global scale.

Responsibilities:

  • Design, build, and deploy AI and machine learning models — including Agentic AI and Generative AI solutions — to solve complex reconciliation and data engineering challenges at enterprise scale.

  • Lead the end-to-end ML model development lifecycle, from requirements gathering and data preprocessing through to ensemble modeling, validation, and production integration.

  • Analyze large volumes of structured and unstructured financial data to uncover trends, patterns, and opportunities for optimization across banking platforms.

  • Define and deliver ML model roadmaps in collaboration with technical and business teams, ensuring alignment with project timelines, budgets, and Citi's architecture standards.

  • Translate complex data findings into clear visualizations and strategic recommendations that inform decisions made by senior business and technology leaders.

  • Partner with engineering, operations, and cross-functional teams to ensure seamless model integration, long-term scalability, and reliable performance in production environments.

  • Identify and communicate technology risks and their business implications, developing mitigation strategies and maintaining transparency with stakeholders at all levels.

  • Maintain comprehensive model documentation and support knowledge transfer to ensure continuity and adoption across teams.

Required Qualifications & Skills:

Technical Expertise:

  • 10+ years hands-on experience in Gen AI/ML development and big data engineering within Financial Services, Insurance, or Telecom environments

  • Expert-level proficiency in Python (scikit-learn, TensorFlow, PyTorch, Pandas, NumPy), and SQL 

  • Deep technical knowledge implementing supervised and unsupervised ML algorithms: linear/logistic regression, neural networks (CNN, RNN, LSTM, Transformers), k-means clustering, DBSCAN, decision trees (CART, C4.5), and ensemble methods (Random Forest, XGBoost, LightGBM, CatBoost)

  • Proven experience building and deploying Agentic AI and LLM-based solutions using:

    • LangGraph for complex agent orchestration and state management

    • LangChain for chain-of-thought reasoning and retrieval-augmented generation (RAG)

    • Agent Development Kit (ADK) for enterprise-grade autonomous agent development

Beneficial Skills & Qualifications:

  • Hands-on experience with advanced statistical modeling: Generalized Linear Models (GLM), Random Forest, Gradient Boosting (AdaBoost, XGBoost), and Natural Language Processing (NLP) techniques including text mining, topic modeling (LDA), and sentiment analysis

  • Experience with model versioning and experiment tracking tools (Mlflow, Weights & Biases, DVC)

  • Proficiency with Git/GitHub/Bitbucket for version control and collaborative development

  • Familiarity with data visualization libraries (Matplotlib, Seaborn, Plotly) and BI tools (Tableau, Power BI)

  • Experience with real-time streaming data frameworks (Kafka, Kinesis)

  • Passion for staying current with emerging AI/ML frameworks, research papers, and open-source contributions

Education:

Bachelor’s or Master’s degree in Computer Science, Data Science, Software Engineering, Information Systems, Mathematics, Statistics or related fields of study.

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Job Family Group:

Technology

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Job Family:

Data Science

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Time Type:

Full time

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Most Relevant Skills

Please see the requirements listed above.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

 

If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.

View Citi’s EEO Policy Statement and the Know Your Rights poster.

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Applicants who checked fit first are 3.1× more likely to hear back

Your match scoreFree · sign in
86Overall
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97Experience

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ASAI compared this JD against 41 signals - skills, seniority, domain, stack overlap etc. Add a resume and it unlocks in about 30 seconds.

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  • Verified jobs, only. Say no to ghost jobs. Your time deserves respect.

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