About the Role
The Data Scientist will lead the development of AI/ML solutions that 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.
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What You Will Do:
- Work with the Data Science team to translate business problems into analytical use-cases with defined outcomes and develop, implement, and test the most appropriate algorithms for these use-cases.
- Collaborate closely with Business Analysts to gather and understand requirements, and work with Data Engineers to build data pipelines and automate/productionize complex ML models to generate insights and recommendations.
- Maintain a strong conceptual understanding of machine learning algorithms including multi-variate regressions, classification algorithms, time series techniques, clustering, NLP, image processing, and optimization models.
- Ensure high coding standards and design standards for reproducibility.
- Drive innovation by enhancing existing solutions and designing new ones while promoting collaboration and awareness in the bank’s analytics community.
- Work with various business units and stakeholders to identify and streamline AI-ML use-cases.
- Deliver end-to-end AI-ML models from development to deployment, including delivery planning, stakeholder communication, and ensuring efficient usage of models for improving decision touchpoints.
- Support ad-hoc requirements in terms of MIS development, building and analyzing SAS Data Models, and streamlining the reporting process through various reporting and analytical tools.
What We Are Looking For:
- Overall 9+ years of experience in analytics, data science, or a similar function.
- 3-4 years of experience in banking analytics.
- Proficiency in Python and SQL is required.
- Experience in end-to-end ML model deployment.
- Familiarity with Machine Learning / Deep Learning / Time-Series / Optimization and Customer Analytics.
Technical Skills:
- Strong coding skills using Python.
- Knowledge of Retail Banking Products.
- Deployment experience across various databases, server/cloud environments (AWS, Azure, APIs, ODBCs, web apps).
- Excellent knowledge of Banking Functional Knowledge is a significant plus.
- Good written, oral communication, and documentation skills with the ability to communicate effectively with stakeholders.
- Expert-level proficiency in relevant tools and technologies.
