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About the Role
The Data Scientist will lead the development of AI/ML solutions to drive data-driven decision-making across customer engagement, marketing, retention, risk, and product functions. This role requires strong analytical expertise, hands-on experience with open-source technologies, and the ability to build interactive applications and deploy models in both batch and real-time environments. The candidate will ensure high-quality delivery, effective stakeholder communication, and adherence to best practices for reproducible, scalable data science.
Responsibilities
- Translate business problems into analytical use-cases with defined outcomes to develop, implement, and test appropriate algorithms.
- Collaborate with Business Analysts for requirement gathering and Data Engineers to build data pipelines and automate/productionize ML models.
- Ensure high coding and design standards for reproducibility.
- Drive innovation by enhancing existing solutions and designing new ones.
- Build collaboration and awareness within the bank’s analytics community.
- Identify and streamline AI-ML use-cases with various business units/stakeholders.
- Deliver end-to-end AI-ML models from development to deployment, including delivery planning and stakeholder communication.
- Ensure efficient usage of models by the business as recommendations for improving decision touchpoints.
- Ensure high coding standards, peer-review, and transparency in work.
- Support ad-hoc requirements for MIS development, building and analyzing SAS Data Models, and streamlining reporting processes.
Requirements
- Overall 9+ years of experience in analytics, data science, or similar function.
- 3-4 years of experience in banking analytics.
- Python and SQL experience required.
- Experience with end-to-end ML model deployment.
- Experience with Machine Learning, Deep Learning, Time-Series, Optimization, and Customer Analytics.
Skills
- Strong coding skills using Python.
- Knowledge on Retail Banking Products.
- Deployment experience (various databases, server/cloud environment: AWS, Azure, and APIs, ODBCs, web apps).
- Excellent knowledge of Banking Functional Knowledge (major plus).
- Good written, oral communication, and documentation skills.
- Ability to communicate effectively with stakeholders.
- Expert-level proficiency in machine learning algorithms including multi-variate regressions, classification algorithms, time series techniques, clustering, NLP, Image Processing, and optimization models.
Experience Level
- 9+ years of experience in analytics, data science or similar function
- 3-4 years of experience in banking analytics