Description :

Role Overview :

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.

Key Responsibilities :

- 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).

Requirements :

- 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.

Nice to Have :

- Background in recommendations/next best action, segmentation, uplift/causal approaches.

- Strong understanding of labeling design for time-based problems (labeling windows, horizons, leakage prevention).

- Practical experience with Databricks.