This is a foundational analytics hire who will help shape how Parker uses data across Risk, Credit, Fraud, Product, Growth, and Finance. You will define how key business and risk questions are measured and turn open-ended questions into durable high-quality analytical systems.
If you want a role where you own important problems end-to-end and your work directly influences capital allocation, credit decisions, and growth strategy — this is it.
What You’ll Do
Design, build and own core analytical metrics and dashboards used by leadership and operating teams
Analyze transaction, customer, and credit data to drive decisions across credit risk,
fraud & AML, portfolio performance, unit economics, and growth
Build automations and data pipelines using SQL and Python (or similar)
Partner closely with Risk, Product, Growth, Finance, and Compliance leaders on high-
impact initiatives
Turn messy, ambiguous questions into clean data, clear metrics and actionable insights
Perform and own business-critical compliance reporting activities for the Risk team
Required Skills and Qualifications
Excellent command of SQL (you can reason about performance, not just write queries)
Strong ability to write Python or similar for data workflows and automation
Strong mental model of data modeling, tables, schemas, and joins
Demonstrated ability to break down ambiguous problems, decide what should be
measured, and build clean, reliable outputs
AI-first approach to create practical applications using Gen AI and LLMs
High ownership mindset: we want you to write your specs and not wait for them
Strong business judgment and curiosity about how companies actually operate
High standards for clarity, correctness, and simplicity
No prior fintech or credit experience is required, but you must show the ability and desire to learn complex domains quickly.
Nice To Have
1–3 years of experience in analytics, data, or technical roles
Experience in fintech, payments, lending, or financial services
Prior work in credit, fraud, risk, or financial analytics
Experience using statistical or data science libraries
Experience with LLMs or AI-assisted analytics / automation workflows
What You’ll Get
Competitive salary
Equity (ESOP) in a fast-growing fintech company
A role with real ownership and real consequences
Direct exposure to credit strategy, risk management, capital allocation, and business
and growth strategy
The chance to build analytics the right way from early stages
Work on applied AI / LLM-driven analytics and automation
A steep growth curve and increasing scope over time
Who Will Thrive Here
Care deeply about doing things correctly, not just quickly
Like messy problems and vague questions
Want to build systems, not just answer one-off questions
Are excited by high responsibility and high standards
Want your work to visibly shape how a fintech company operates