Principal Data Scientist - Fintech Analytics
Intuit
Principal Data Scientist – Fintech Analytics
Company Overview
Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With approximately 100 million customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.
Job Overview
At Intuit, we are building the financial operating system that powers money movement across our ecosystem—QuickBooks, TurboTax, Credit Karma, and Mailchimp. The Fintech Platform team sits at the center of this mission, enabling secure, reliable, and scalable movement of billions of dollars annually across payments, banking, balance, lending, and global rails.
We are seeking a Principal Data Scientist, Fintech Analytics to lead data science and decision intelligence for our money movement platforms. This is a highly visible, high-impact role responsible for transforming complex transactional data into predictive insights that improve reliability, revenue, risk management, and customer trust.
This role goes far beyond dashboards or retrospective analysis. You will act as a thought partner to Fintech product, engineering, risk, finance, and operations leaders, owning analytical strategy across performance, fraud, declines, funds availability, and platform health. Your work will directly influence platform architecture decisions, risk posture, investment prioritization, and long-term growth.
Responsibilities
- Lead principal-level data science initiatives across Intuit’s Fintech money movement platforms, spanning payments, balance, banking, lending, and global rails
- Build and evolve predictive and diagnostic models to understand and improve transaction success, authorization rates, latency, fraud losses, and funds availability
- Own business and platform observability from a data science lens—connecting system behavior to customer impact, revenue outcomes, and risk exposure
- Partner deeply with Product, Engineering, Risk, Finance, and Operations leaders to shape data-informed strategy and trade-offs
- Drive root-cause analysis for complex, ambiguous issues such as payment declines, anomaly detection, fraud spikes, reconciliation gaps, and cross-rail performance differences
- Develop frameworks to quantify business impact during incidents and systemic changes, enabling faster and better executive decision-making
- Influence roadmap and investment decisions by translating model outputs into clear narratives, scenarios, and recommendations
- Establish best practices for model governance, metric definitions, experimentation, and analytical rigor across Fintech
- Mentor and elevate other data scientists and analysts through technical leadership, reviews, and knowledge sharing
Qualifications
- 10+ years of experience in data science, applied machine learning, or quantitative analytics, with ownership of mission-critical systems
- Strong experience working with large-scale transactional or event-driven data, ideally in fintech, payments, banking, or other regulated financial domains
- Deep understanding of money movement concepts such as payment rails, authorization flows, settlement, reconciliation, fraud, chargebacks, and funds availability
- Proven track record of building models that drive real business outcomes, not just academic or offline results
- Advanced proficiency in SQL and strong experience with Python (or equivalent) for data science and modeling
- Experience with anomaly detection, forecasting, classification, causal analysis, or optimization in production environments
- Exceptional ability to translate complex analyses into clear, executive-level insights
- Comfortable operating in ambiguity, owning problems end-to-end from formulation to impact
- Bachelor’s degree in a quantitative field (Engineering, Computer Science, Mathematics, Statistics, or equivalent); advanced degree preferred but not required
Why This Role Matters?
This role is foundational to Intuit’s ability to operate and scale a trusted financial platform. The Principal Data Scientist will be a single-threaded owner for understanding and predicting how billions of dollars move through our systems, enabling Intuit to proactively manage risk, maximize revenue, and deliver exceptional customer experiences at scale.
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:
Bay Area California $ 240,000- 324,500