The Staff 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. The 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 Data Science team to translate given business problem into analytical use-cases with defined outcomes to develop, implement and test most appropriate algorithms for a given use-case.
- Work closely with Business Analyst for requirement gathering/understanding and work with Data Engineers to build data pipelines and automate/productionize complex ML models to insights and recommendations.
- 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 as well as designing standards to ensure reproducibility.
- Drive innovation by enhancing existing solutions and designing new ones and build collaboration and awareness in the bank’s analytics community.
- Deliver end-to-end AI-ML models from development to deployment with delivery planning, communications with stakeholders, and ensuring efficient usage of the models by the business as recommendations for improving decision touchpoints.
- Support ad-hoc requirement in terms of MIS development, building and analyzing data models, streamlining the reporting process through various reporting and analytical tools.
Requirements
- Overall 7+ years of experience in analytics, data science, or similar function.
- 3-4 years of experience in banking analytics.
- Python and SQL experience required.
- Worked on end-to-end ML model deployment.
- Strong coding skills using Python.
- Knowledge of 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, documentation skills with the ability to communicate effectively with stakeholders.
- Expert-level proficiency in Python with SAS/R/Spark as a plus.
