Senior Staff Data Scientist (AI/ML)

TL;DR

Senior Staff Data Scientist (AI/ML): Building and enhancing advanced data foundations and toolkits for the analytics community with an accent on scalable modeling frameworks and AI strategy. Focus on quantifying financial impact of customer friction, advancing generative AI capabilities, and influencing executive-level decisions.

Location: Mountain View, California or San Diego, California

Company

Global financial technology platform powering prosperity for 100 million customers via products like TurboTax, Credit Karma, QuickBooks, and Mailchimp.

What you will do

• Formulate hypotheses and define key metrics to quantify financial and operational impacts of customer friction.
• Build advanced statistical and machine learning models to analyze data across segments and business units.
• Develop prioritization frameworks to inform product roadmaps and resource allocation.
• Partner with senior leadership (VP/Director level) to embed data-driven decision-making into core operating mechanisms.
• Advance generative AI and automation to scale insight generation across the organization.
• Mentor team members and elevate technical standards across cross-functional partners.

Requirements

• 10+ years of experience in data science, ML, or advanced analytics with measurable business impact.
• Expert proficiency in SQL and Python (or R) for building production-ready, reproducible workflows.
• Deep expertise in statistical modeling, including regression, classification, causal inference, and experimentation at scale.
• Strong experience applying NLP and ML techniques to large-scale unstructured data.
• Degree in Statistics, Mathematics, Computer Science, or a related quantitative field (PhD preferred).
• Must be based in or able to work from Mountain View, CA or San Diego, CA.

Culture & Benefits

• Competitive compensation package with a strong pay-for-performance rewards approach.
• Eligibility for cash bonuses and equity rewards.
• Comprehensive corporate benefits program.
• Commitment to fair pay and diversity across ethnicity and gender.