Staff Data Analyst

Join Self, a fintech company focused on driving sustainable growth throughout the customer lifecycle. As a Staff Data Analyst, you will have company-wide ownership of metrics and analytical systems in the Credit Builder Account and Credit Card portfolio. You will lead analytical projects, contribute to data models, partner with various teams, and develop business intelligence dashboards. The role requires a strong analytical background, experience in data analytics, and a passion for AI and emerging technologies.

• Lead analytical projects and experiments to identify actual drivers of customer and product behavior, segmentation, and engagement.
• Contribute directly to the data models for the Credit Builder Account and Credit Card portfolio, in partnership with Data Engineering and Analytics Engineering.
• Build and manage agentic AI and semantic workflows to enable working smarter and automation of day-to-day functions.
• 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 must be comfortable influencing teams and having a strong point-of-view that is loosely held but informed by data
• 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
• 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
• 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
• 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
• 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
• 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
• Experience working with analytics engineering ELT tools (e.g., dbt, Databricks, Airflow, Git)
• Experience building dashboards and reports using BI tools (e.g., Tableau, Looker, Power BI)
• Ability to translate business questions into actionable insights and clearly explain technical concepts to non-technical audiences
• 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
• Bachelor's or Master's degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, or a related discipline
• Excellent analytical, problem-solving, critical thinking and communication skills
• Strong proficiency in at least one programming language for data analysis (e.g., Python, R)
• Experience working in cloud-based data warehouses with proven expertise in SQL (e.g., Snowflake, Redshift, BigQuery)
• Experience with AI (e.g., Claude, Codex), including building skills, agents, and context harnesses
• 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)
• Self Financial requires all employees hired to successfully pass a background check
• Understanding of customer lifetime value (CLTV) modeling and cohort analysis
• Familiarity with marketing automation platforms and customer data platforms
• Experience with predictive modeling techniques (e.g., regression, classification) and machine learning concepts
• Experience working in an agile development environment