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About the Role

Lead the development of AI/ML solutions to drive data-driven decision-making across customer engagement, marketing, retention, risk, and product functions. 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.
• Automate and productionize complex ML models to generate insights and recommendations.
• 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 including MIS development, SAS Data Model analysis, and reporting process streamlining.

Requirements

• Overall 7+ years of experience in analytics, data science, or similar function.
• 3-4 years of experience in banking analytics.
• Experience with end-to-end ML model deployment.
• Strong conceptual understanding of machine learning algorithms including multi-variate regressions, classification algorithms, time series techniques, clustering, NLP, Image Processing, and optimization models.
• Knowledge on Retail Banking Products.
• Excellent knowledge of Banking Functional Knowledge (major plus).

Skills

• Python
• SQL
• Machine Learning
• Deep Learning
• Time-Series Analysis
• Optimization
• Customer Analytics
• Deployment experience (various databases, server/cloud environment: AWS, Azure, and APIs, ODBCs, web apps)
• Written communication
• Oral communication
• Documentation skills
• Stakeholder communication
• SAS (plus)
• R (plus)
• Spark (plus)

Experience Level

• 7+ years of experience in analytics, data science or similar function
• 3-4 years of experience in banking analytics