Global Cards Solutions Data Scientist

Payments analytics specialist focused on debit and credit card portfolios, using strong quantitative and coding skills to analyze complex transactional data. Apply advanced analytics and predictive modeling to drive data‑informed decisions, enhance the cardholder experience, improve operational efficiency, and deliver actionable insights aligned with strategic business goals.

This position is hybrid.

NYC Salary Range: $105,000 - $130,000 annually: compensation is commensurate to geographic location.

• Uphold UNFCU’s mission, core values, and guiding principles by providing an exceptional service experience to colleagues and members alike through consistent demonstration of our service excellence behaviors.
• Partner cross-functionally to translate business objectives into actionable analytics initiatives that drive portfolio growth, efficiency, and profitability.
• Develop and deploy predictive models and advanced segmentation strategies to optimize acquisition, engagement, retention, and overall card portfolio performance.
• Analyze large, complex datasets to identify trends, risks, operational gaps, and growth opportunities across credit and debit portfolios.
• Monitor financial and operational KPIs, delivering insights to improve profitability, credit performance, fraud management, and operational effectiveness.
• Identify and implement data‑driven process improvements across servicing, marketing, and portfolio management to streamline operations and enhance controls.
• Design and evaluate controlled tests, forecasting models, and profitability analyses to support strategic planning and data‑informed decision‑making.
• Build dashboards and executive‑ready presentations that translate complex analyses into clear, actionable insights for both technical and non‑technical stakeholders.
• Ensure compliance with federal and state laws and regulations and UNFCU’s Code of Ethics & Business Conduct.
• Collaborate effectively across business lines while taking full ownership of initiatives in a self‑driven manner.

• Bachelor’s degree
• 8-10 years of data science experience in the financial domain
• Strong analytical ability to transform large, complex datasets into actionable business insights.
• Expertise in cohort analysis, segmentation, decile analysis, campaign evaluation, and portfolio optimization.
• Experience developing predictive models to support acquisition, retention, engagement, and profitability strategies.
• Solid applied statistical knowledge, including regression, hypothesis testing, and time series forecasting (ARIMA, Prophet).
• Advanced programming skills in Python (Pandas, Num Py), R, and SQL for data extraction, analysis, and modeling.
• Proficiency in business intelligence tools (e.g., Tableau) and effective data visualization techniques.
• Skilled in experiment design, reproducible analytics workflows, data storytelling, stakeholder communication, and end-to-end project management.