Senior Data Scientist, Product Analytics

About the role

You will own the design and execution of analytics that directly influence how consumers navigate the hardest moments in their financial lives. Your work will transform raw interaction data into narratives that change how people move through collections. You will partner with product managers to define the questions that matter most and build the frameworks that turn uncertainty into clarity. Through modeling and experimentation, you will uncover the levers that drive sustainable repayment and responsible outcomes for consumers. You will ensure that every decision is grounded in evidence rather than intuition, making the data backbone of the business impossible to ignore. By visual complex patterns and communicating findings with precision, you will empower teams to act with confidence and speed. In this role, you will be a critical bridge between the emergency room of collections and the promise of long term financial health.

Key facts

What you'll do

• Partner with product managers to translate ambiguous problems into rigorous analytical roadmaps that test core hypotheses about consumer behavior.
• Design and run experiments that measure the impact of product changes on repayment outcomes, using statistical methods to isolate true effects.
• Build and maintain dashboards that track key performance indicators across the consumer journey, enabling teams to monitor health in real time.
• Conduct deep dives into funnel and cohort analysis to uncover where users drop off and why, turning observations into prioritized opportunities.
• Develop predictive models that surface risk and propensity to engage, helping the business focus efforts where they will have the highest impact.
• Translate advanced analytical findings into clear narratives and visualizations that make complex tradeoffs understandable to non-technical stakeholders.
• Collaborate closely with operations and client success teams to ensure data insights are actionable in live conversations with consumers.
• Champion data literacy across the organization, establishing standards and documentation that allow others to explore the data on their own.
• Maintain a rigorous approach to measurement, ensuring that definitions, logic, and assumptions are consistent and defensible over time.
• Explore new tools and techniques, testing how emerging approaches can improve speed, accuracy, and reliability in a high stakes environment.
• Work backwards from business goals to define metrics, then validate whether initiatives move those metrics in the intended direction.
• Partner with cross functional stakeholders to scope projects, identify dependencies, and anticipate downstream implications of analytical decisions.
• Document methodologies and results so that insights can be reproduced, challenged, and built upon by future analysts.
• Act as an internal thought partner, bringing evidence based perspectives to debates about product direction and operational strategy.

Requirements

You must have at least 2 years of experience using SQL to query, transform, and derive insights from complex datasets. You bring experience using languages like Python or R to conduct statistical analysis and translate business questions into testable models. You have a medium to advanced understanding of statistics as they relate to experimentation, including concepts like bias, confounding, and measurement error. You are comfortable working with messy, real world data and able to build reliable pipelines that stakeholders can trust. You can present data in a compelling way to empower product and engineering teams to make better decisions with confidence. You think strategically and consider the impact of your work on the success of the business as a whole, not just the immediate project. You are able to work independently, given context and some initial guidance, diving deep into problems and making insightful recommendations for the business. You communicate clearly and professionally, adapting your style for executives, operators, and technical collaborators. You are comfortable collaborating in a fast moving, decentralized environment where decisions are made close to the problem. You are committed to building products that serve consumers responsibly and understand the gravity of working in consumer finance.

Nice to have

Experience working with regulated financial products and understanding of compliance constraints around data usage and consumer communication. Familiarity with collections specific metrics, workflows, and regulatory environment. Experience building and maintaining internal tooling that supports data exploration and reporting efficiency. Background in A B testing methodology and causal inference in operational settings. Exposure to natural language processing or voice interaction data in customer facing products.

Practical notes

This role is based in our New York City office and requires in person presence. We operate a minimum of three days per week in office in Nolita to enable collaboration, cross pollination, and relationship building. Travel is not required for this role. The position is full time and aligned with standard working hours, with flexibility to manage personal needs within team norms. We use our own products and internal systems, and you will be expected to engage with them as part of your daily workflow.