Senior Staff Data Scientist (Personal Finance)

Location: Oakland, California or Mountain View, California, United States

Base salary: $210,500–$284,500 per year, with potential cash bonus, equity rewards, and benefits.

Company

hirify.global is a financial technology platform behind products including TurboTax, Credit Karma, QuickBooks, and Mailchimp.

What you will do

• Define the analytics and measurement strategy for the Insurance business across the end-to-end member journey.
• Partner with Product, Marketing, Engineering, AI Science, and senior business leaders to shape priorities and investment decisions.
• Lead experimentation, causal inference, incrementality measurement, and funnel optimization.
• Improve targeting, ranking, matching, and personalization for insurance experiences.
• Establish metrics and measurement frameworks covering acquisition, engagement, conversion, retention, member value, and economics.
• Build reusable analytical frameworks, datasets, and tools while mentoring Data Scientists and raising scientific standards.

Requirements

• 9+ years of experience in data science and analytics, with measurable impact across complex customer journeys or multiple initiatives.
• Deep expertise in experimentation, causal inference, customer segmentation, funnel optimization, and measurement.
• Experience applying machine learning techniques such as classification, regression, ranking, targeting, or propensity modeling.
• Ability to translate ambiguous business problems into analytical strategies and actionable decisions.
• Experience creating reusable analytical frameworks and capabilities adopted beyond an individual project or team.
• Exceptional communication and stakeholder influence skills with Director- and VP-level leaders.

Culture & Benefits

• Competitive compensation with a pay-for-performance rewards approach.
• Potential cash bonus, equity rewards, and benefits according to applicable plans and programs.
• Opportunity to influence Insurance and the broader Personal Finance organization through scalable scientific capabilities.