Senior Manager

JD :
Senior Manager, Data Science (Corporate/SME)

Banking Domain

Exp : 5+ years

We are looking for a Senior Manager, Data Science, focused on building and scaling data science solutions for Corporate/SME clients. The role requires end-to-end ownership from problem framing and dataset creation to modeling, deployment, and monitoring in production.

• Lead end-to-end delivery of DS/ML solutions for Corporate/SME (including propensity use cases).
• Partner with Business stakeholders to define problem statements, success metrics, and delivery plans.
• Independently extract, prepare, validate data, and build training datasets.
• Design and implement robust pipelines for preprocessing, feature engineering, model training, and evaluation.
• Ensure solution quality: correct labeling design, leakage prevention, validation, and ongoing performance monitoring.
• Collaborate closely with Data Engineering: define requirements, manage dependencies, and troubleshoot pipelines.
• Establish and uphold DS standards within the team (best practices, documentation, review processes, mentoring).

• Strong experience applying Data Science/ML in banking, with exposure to Corporate/SME business contexts.
• Hands‑on proficiency with IBM Cognos to independently extract and prepare data.
• Advanced SQL skills (including window functions) and Python skills (data science packages).
• Deep understanding of the end-to-end ML lifecycle: preprocessing, feature engineering, modeling , evaluation, production/monitoring.
• Solid foundation in ML algorithms and the ability to explain model choices, trade‑offs, and limitations.
• Proven experience deploying models to production and applying MLOps practices (e.g., MLflow/registry, CI/CD, monitoring).
• Excellent stakeholder management, communication, and prioritization skills.

• Background in recommendations/next best action, segmentation, uplift/causal approaches.
• Strong understanding of labeling design for time‑based problems (labeling windows, horizons, leakage prevention).