Data Scientist II, Enterprise Payments Data & Analytics
About The Position
The Enterprise Payments Data & Analytics team within AI2 (Analytics, Insights, and AI) is responsible for delivering data and insights that support the modernization, monitoring, and optimization of core payment processes across the bank. We partner closely with business and technology teams to enable end-to-end visibility into the performance of payment products, strengthen governance, and drive data-driven decision making through building scalable data pipelines and enterprise dashboards, enhancing operational monitoring and reporting, and supporting large-scale transformation programs to improve efficiency, resilience, and client experience across payment platforms. The Data Scientist II, Enterprise Payments Data & Analytics, will design, build, and deploy analytics solutions across cloud-based platforms, translating complex business problems into production-ready data assets, insights, and automated analytics. This role combines strong technical expertise, analytical thinking, and business partnership to deliver measurable outcomes across operations, risk, and performance management.
Requirements
- Undergraduate degree in quantitative or technical discipline such as Mathematics, Statistics, Computer Science, Engineering, or Finance
- 3+ years of hands-on experience in Data Science or Data Engineering roles, delivering scalable analytics solutions in complex environments
- Strong programming skills in Python and SQL, with proven experience working with large and complex datasets
- Experience with enterprise-scale cloud data platforms and understanding of associated tools, data structures, controls, and constraints (Azure Databricks is preferred)
- Proven ability to apply statistical methods, machine learning techniques, and data wrangling to solve business problems and generate actionable insights
- Experience designing and delivering data visualizations and dashboards (e.g., Power BI) to communicate insights to both technical and non-technical stakeholders
- Strong business acumen with the ability to translate ambiguous requirements into structured analytical solutions
- Demonstrated experience working in cross-functional teams, including collaboration with business stakeholders, data engineers, and technology partners
- Excellent communication and storytelling skills, with the ability to influence decision-making through data
Responsibilities
- Develop scalable analytics solutions using Python, SQL, PySpark and PowerBI within cloud environments (Azure Databricks and enterprise data platforms)
- Build curated datasets, automated pipelines, and analytics layers that support operational monitoring, performance insights, and regulatory controls
- Analyze large, complex datasets to identify trends, risks, gaps, and optimization opportunities
- Translate ambiguous business questions into structured analytical frameworks and actionable deliverables
- Embed data quality checks, validation, and automation into all analytics products
- Partner cross-functionally with business stakeholders, data engineering teams, and enterprise analytics groups
- Communicate insights through dashboards, presentations, and executive-ready storytelling
- Continuously improve analytics processes, standards, and reusable data assets
- Support a strong risk and control culture through robust analytical monitoring and governance
Benefits
- health and well-being benefits
- savings and retirement programs
- paid time off
- banking benefits and discounts
- career development
- reward and recognition programs
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
