<span><p>We are looking for a<span></span><strong>Product Data Scientist</strong><span></span>to partner closely with Credit Cards and Banking product teams, shaping product strategy and driving growth through rigorous analysis, experimentation, and applied machine learning.</p><p>You’ll work alongside Product Managers, Engineers, and business stakeholders to identify opportunities, influence product decisions, and measure the impact of new features — from optimizing how consumers discover and compare financial products to developing predictive tools such as approval odds and personalized recommendations.</p><p>This is a hands-on, highly analytical role for someone comfortable exploring complex data, challenging product assumptions, designing experiments, and translating insights into decisions that ship.</p><p><br></p><p><strong>What you’ll do</strong></p><p><em>Product strategy &amp; growth</em></p><ul><li>Partner with Product Managers and vertical leadership to identify, size, and prioritize growth opportunities across the consumer journey.</li><li>Establish metric frameworks — north-star metrics, funnel definitions, and performance drivers.</li><li>Lead deep-dive analyses to understand consumer behavior, friction points, and performance trends.</li><li>Translate ambiguous business questions into clear analytical approaches and actionable recommendations.</li></ul><p><em>Experimentation &amp; applied data science</em></p><ul><li>Own the full experimentation lifecycle — hypothesis development, test design, statistical analysis, and business impact measurement.</li><li>Develop predictive and statistical models that improve consumer experiences.</li><li>Collaborate with Product and Engineering teams to translate findings into consumer-facing features.</li></ul><p><em>Analytics practices &amp; tooling</em></p><ul><li>Use SQL, Python, Databricks, and BI tools to deliver analyses and reporting.</li><li>Build and maintain metric definitions, dashboards, and measurement frameworks.</li><li>Automate recurring analytical processes.</li><li>Communicate findings clearly to both technical and non-technical stakeholders.</li><li>Promote a data-driven product development culture across teams.</li></ul><p><br></p><p><strong>Required skills &amp; experience</strong></p><ul><li>3+ years of professional experience in data science, product analytics, or a related analytical discipline — with demonstrated experience influencing product decisions through data.</li><li>Strong proficiency in SQL and Python for data exploration, statistical analysis, automation, and predictive modeling.</li><li>Hands-on experience with Databricks for analytical workflows, data processing, or model development — required.</li><li>Proven experience designing, analyzing, and interpreting A/B tests, including statistical significance, power analysis, and common experimentation pitfalls.</li><li>Strong understanding of product analytics — funnel optimization, metric development, cohort analysis, and behavioral segmentation.</li><li>Working knowledge of applied statistics and machine learning techniques — regression, classification, propensity modeling, and/or causal inference.</li><li>Experience developing dashboards and automating analytical workflows using modern BI and data tools.</li><li>Excellent communication and collaboration skills — able to influence Product Managers, Engineers, and business stakeholders through data-backed recommendations.</li><li>Bachelor’s or advanced degree in Statistics, Mathematics, Economics, Computer Science, Engineering, or a related quantitative discipline, or equivalent practical experience.</li></ul></span>