Senior Staff Data Scientist, Personal Finance

Intuit · FinTech · Banque & Paiement · Oakland, California, United States / Mountain View, California, United States

Oakland, California, United States / Mountain View, California, United StatesInfra & Data16 septembre 2026Lu sur Radancy
CDISur siteStaff / Principal

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Description

We are seeking a Senior Staff Data Scientist to serve as the analytical leader and strategic thought partner for our Insurance business. This is a high-impact individual contributor role where you will set the analytics and measurement vision, raise the scientific bar, and influence the product, marketing, and business strategy for Insurance.

You will partner closely with senior leaders across Product, Marketing, Engineering, AI Science, and our insurance ecosystem to identify the biggest opportunities across the end-to-end member journey—from creating awareness and intent, to improving shopping and matching, to driving conversion and delivering measurable member value.

The ideal candidate combines deep analytical and scientific expertise with strong business judgment. You will operate effectively in ambiguity, connect insights across initiatives, and translate complex customer and marketplace dynamics into strategies that drive both member and business outcomes.


Responsibilities

  • Set the analytics strategy for Insurance: Define the analytical and measurement vision across the end-to-end insurance journey, translating business strategy into a portfolio of high-impact data science opportunities.
  • Influence business and product strategy: Serve as a strategic thought partner to senior Product, Marketing, and business leaders, using data, customer insights, and external trends to shape priorities and investment decisions.
  • Build durable customer and marketplace understanding: Connect insights across behavioral data, experiments, models, and external signals to understand insurance needs, shopping behavior, price sensitivity, conversion, and member value.
  • Lead experimentation and causal measurement: Establish rigorous approaches to measuring incrementality across the insurance funnel, including complex experiments and causal inference methodologies where traditional A/B testing is constrained.
  • Advance personalization and matching: Partner with Product and AI Science to improve targeting, ranking, matching, and personalization—helping connect members with the right insurance opportunities at the right time.
  • Shape the AI-native Insurance roadmap: Co-create the analytics and AI strategy for emerging insurance experiences, establishing measurement frameworks that connect model and experience quality to member and business outcomes.
  • Define the measurement architecture: Establish the metrics, leading indicators, and frameworks used to evaluate the health of the Insurance business, including acquisition, engagement, conversion, retention, member savings/value, and economics.
  • Identify and size new growth opportunities: Use first-principles analysis to uncover opportunities across the funnel, quantify their potential impact, and help leadership prioritize where to invest.
  • Build scalable scientific capabilities: Develop reusable frameworks, methodologies, datasets, and analytical tools that improve decision-making across Insurance and can scale to the broader Personal Finance organization.
  • Raise the scientific bar and develop talent: Mentor and elevate Data Scientists, establish analytical best practices, contribute to hiring and calibration, and scale your impact through others while remaining hands-on in the highest-leverage problems.

Qualifications

We’re looking for a strategic, curious, and influential data science leader who can combine scientific depth with strong business judgment.

  • 9+ years of experience in data science and analytics, with a track record of driving strategy and measurable business impact across multiple initiatives or complex customer journeys.
  • Demonstrated ability to apply first-principles thinking to translate ambiguous business problems into analytical strategies and actionable decisions.
  • Deep expertise in experimentation, causal inference, customer segmentation, funnel optimization, and measurement, with the judgment to balance statistical rigor with business realities.
  • Experience applying machine learning techniques—including classification, regression, ranking, targeting, or propensity modeling—to customer and business problems.
  • Proven ability to connect insights across multiple analyses and initiatives to develop a broader understanding of customer behavior and influence product or business strategy.
  • Experience creating reusable analytical frameworks, methodologies, and capabilities that are adopted beyond an individual project or team.
  • Exceptional communication and stakeholder influence skills, with demonstrated ability to influence Director- and VP-level leaders across business and technical organizations.

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:
Oakland $210,500 - $284,500

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Publiée le 16 septembre 2026 · vue pour la première fois le 16 septembre 2026

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