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Citi is seeking a Lead Gen AI/ML Data Scientist to join the Olympus Data Reconciliation and Engineering team in Chennai. You will drive the full ML lifecycle from ideation to deployment, shaping enterprise-scale AI capabilities across global processing hubs.
You will work with advanced models, supervise data workflows, and communicate insights to senior stakeholders, ensuring production-ready solutions and scalable analytics.
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.
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.
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 inPython(scikit-learn, TensorFlow, PyTorch, Pandas, NumPy),andSQL
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 deployingAgentic AIandLLM-based solutionsusing:
LangGraphfor complex agent orchestration and state management
LangChainfor chain-of-thought reasoning and retrieval-augmented generation (RAG)
Agent Development Kit (ADK)for enterprise-grade autonomous agent development
Hands-on experience with advanced statistical modeling:Generalized Linear Models (GLM),Random Forest,Gradient Boosting(AdaBoost, XGBoost), andNatural Language Processing (NLP)techniques including text mining, topic modeling (LDA), and sentiment analysis
Experience withmodel versioning and experiment tracking tools(Mlflow, Weights & Biases, DVC)
Proficiency withGit/GitHub/Bitbucketfor version control and collaborative development
Familiarity withdata visualization libraries(Matplotlib, Seaborn, Plotly) andBI tools(Tableau, Power BI)
Experience withreal-time streaming dataframeworks (Kafka, Kinesis)
Passion for staying current with emerging AI/ML frameworks, research papers, and open-source contributions
Bachelor’s or Master’s degree in Computer Science, Data Science, Software Engineering, Information Systems, Mathematics, Statistics or related fields of study.
Technology
Data Science
Full time
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