Chime was created because we believe everyone can unlock financial progress, and we want to develop solutions and services to empower people to succeed. The premise upon which we started Chime is simple: basic banking services should be helpful, transparent, and easy. Our easy-to-use tools and intuitive platforms give members the ability to have more control over their money and to take action toward achieving their financial ambitions.

By designing a member-centric banking app with easy-to-understand financial tools, we’re creating a more competitive market with options for everyday Americans. We offer access to accounts with no overdraft fees, provide members the chance to receive their pay up to 2 days early* with direct deposit, help them build credit history, and build financial literacy to hit their goals—among many other things.

Since 2012, we’ve grown our team to more than 1300 Chimers across 3 offices. But more than that, we’ve expanded the products and services we offer to our members based on member feedback. And in doing so, we’ve disrupted the banking industry and changed the conversation for everyday people about money on a national level.

Chime is a financial technology company, not a bank. Banking services are provided by The Bancorp Bank, N.A. or Stride Bank, N.A., Members FDIC.

*Early access to direct deposit funds depends on the timing of the submission of the payment file from the payer. We generally make these funds available on the day the payment file is received, which may be up to 2 days earlier than the scheduled payment date.

About the Role
As a member of the Chime Enterprise Product team you will have the opportunity to help develop, test, launch and scale both member rewards and earned wage access products. Through experimentation, user behavior analysis, sophisticated statistical and data science modeling, and dashboard development, you will surface product insights to increase enrollment, adoption, and retention of our users.

In this role, you will work closely with product managers, user research, engineers, product & lifecycle marketing, and operational stakeholders to foster a data-driven product development culture, advise our product roadmaps, and build a deep understanding of member behavior.

In this role, you can expect to
Keep a pulse on performance metrics and KPIs. You will be positioned to have a view of the business, product, and member base and encouraged to understand and explain trends.
Drive predictive analytics and user behavior modeling, identifying trends and opportunities to improve user experiences, increase reward redemptions, and maximize engagement with key product features.
Take initiative in designing and executing experiments, including A/B testing and data-driven initiatives, to evaluate the effectiveness of features like personalized goal-setting and tiered rewards in influencing user behavior.
Own the measurement of product impact, developing frameworks for understanding causation, attribution, and incremental lift, ensuring alignment with the product’s engagement and retention goals.
Collaborate with product, marketing and operational teams to deliver actionable insights and ensure alignment on strategy, goals, and metrics, contributing to data integrity and the success of key initiatives.

To thrive in this role, you have
4+ years in data-focused roles (post-internship), building analytical infrastructure and data tools that support a wide audience and facilitate decisions of trade-offs. B2C product analytics and FinTech experience preferred.
Strong quantitative background (e.g., Statistics, Economics, Applied Mathematics) with experience in statistical analysis, causal inference, and hypothesis testing
Expertise in SQL - you innately translate business questions to queries, understand the edge cases of joins, and can explore a warehouse to find data most appropriate to the problem.
Experience leading experimentation, statistical analysis, and sophisticated measurement (e.g. causal inference) E2E to guide decision making.
Competence in Python or R for data analysis and modeling.
Hands-on experience with data visualization tools (e.g., Tableau, Looker) and the ability to create clear and impactful visualizations.
Familiarity with cloud and infrastructure services like AWS, Snowflake, DBT, etc. is preferred
Understanding of statistical concepts (e.g. regression, decision tree) and a willingness to learn experimental design.
Strong problem-solving skills and attention to detail.
Excellent communication skills, with the ability to explain technical concepts to non-technical audiences.
Interest in financial products and improving financial inclusivity.