Staff Data Analyst

Role Summary:

Self is looking for a Staff Analyst to join our Product and Customer Analytics team for our most important problem, driving sustainable growth throughout the customer’s lifecycle. This role is for a builder who works backwards from having a deep understanding of how the business functions, what data it takes to build that understanding, and then applying a deep analytical lens.

You will have company-wide visible ownership of the metrics and analytical systems in the Credit Builder Account and Credit Card portfolio as well as the Customer lifecycle itself. You must be comfortable influencing teams and having a strong point-of-view that is loosely held but informed by data.

You are joining a highly AI Native team with high autonomy across data modeling, analysis, and predictive use cases. You are expected to be comfortable with semantic layer build outs, and the core tenets of what it takes to build an AI native analytics platform that enables high velocity with high trust decision making.

What you will do:

• Lead analytical projects/experiments that get past correlation to the actual drivers of customer and product behavior, segmentation, and engagement. Understanding which movements are noise versus those we should act on.
• Contribute directly to the data models this portfolio runs on, in partnership with Data Engineering and Analytics Engineering.
• Partner closely with Product, Marketing, and Engineering teams to define measurement strategies, set goals, and influence the business roadmap.
• Build and manage agentic AI (Claude), domain context layers, and semantic workflows (dbt Metric Flow, Semantic Layer) to enable working smarter and automation of day-to-day functions.
• Develop and maintain business intelligence dashboards and reporting that provide visibility into key lifecycle marketing KPIs, customer cohorts, and campaign performance.
• Utilize advanced analytical techniques (e.g., statistical modeling, predictive analytics, causal inference) to uncover insights and forecast the impact of initiatives.
• Communicate findings and recommendations effectively to both technical and non-technical audiences, including senior leadership.
• Stay abreast of industry trends in financial products, AI, analytics, analytics engineering, and business intelligence.

Who You Are:

• Outcome & Impact Focused: You understand that your success ultimately depends on your impact, you are driven by the desire to create tangible business results. You prioritize initiatives that will have the greatest impact.
• Dedicated Work Ethic: You are willing to dive deep into the data, tackle challenging problems head-on, and see projects through to completion with rigor and attention to detail.
• Innovator & AI Enthusiast: You are curious about emerging technologies, including AI, and eager to explore how they can be applied to improve analytical processes, models, and marketing effectiveness.
• Hungry for Growth: You have a strong desire to continuously learn, expand your skillset, and seek out new challenges. You are proactive in your own development.
• Thrives in Ambiguity: You are comfortable navigating complex, sometimes undefined problems and can bring structure and clarity to ambiguous situations in a fast-paced environment.
• Real Ownership Mentality: You take full responsibility for your work, from initial analysis to communicating results and influencing action. You treat every challenge as an opportunity to make a difference.

Qualifications:

• Bachelor's or Master's degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, or a related discipline.
• 8+ years of experience in a data analytics role, with significant experience supporting product teams, preferably within fintech or a related consumer-facing industry (e.g., banking, credit cards, lending).
• Experience working in cloud-based data warehouses with proven expertise in SQL (e.g., Snowflake, Redshift, BigQuery).
• Experience building dashboards and reports using BI tools (e.g., Tableau, Looker, Power BI).
• Experience working with analytics engineering ELT tools (e.g., dbt, Databricks,  Airflow, Git)
• Experience with AI (e.g., Claude, Codex), including building skills, agents, and context harnesses.
• Strong proficiency in at least one programming language for data analysis (e.g., Python, R).
• Experience with A/B testing and causal inference, including both Bayesian and Frequentist approaches and quasi-experimental methods (difference-in-differences, etc.) for cases where a clean test isn't an option.
• Excellent analytical, problem-solving, critical thinking and communication skills.
• Ability to translate business questions into actionable insights and clearly explain technical concepts to non-technical audiences.

Preferred Skills:

• Familiarity with marketing automation platforms and customer data platforms.
• Experience with predictive modeling techniques (e.g., regression, classification) and machine learning concepts.
• Understanding of customer lifetime value (CLTV) modeling and cohort analysis.
• Experience working in an agile development environment.

What's Exciting About the Role:

• Direct Impact: Your analysis and insights will directly shape how we engage with our customers, influencing key marketing strategies and product decisions that help people improve their financial health.
• Challenging Problems: You'll tackle complex analytical challenges related to customer behavior, segmentation, and optimization in a fast-paced, data-rich environment.
• Strategic Partnership: Work closely with marketing and product leaders, acting as a trusted advisor to drive growth and improve the customer experience.
• Growth Opportunities: This Staff role offers the chance to lead significant projects, mentor others, and contribute to the strategic direction of the Analytics team.
• Meaningful Mission: Be part of a company with a mission to make a real difference in people's lives by providing tools to build credit and achieve financial stability.

Base salary range: $140,000 - $170,000 annually.  Individual pay is based on factors unique to each candidate, including skill set, experience, and other job-related reasons.