Senior Staff Data Scientist, Lending

Intuit

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Mountain View, CASan Francisco, CA
Salary: $210,500–$284,500 / yr
Posted: 1 day ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $181k

This role $248k

$116k most similar roles pay here $303k

This role pays more than 89% of similar roles. Most pay $143,697–$218,250 — the shaded band above. At the midpoint, this role pays about $248k versus about $181k for comparable roles.

Based on 240 similar postings.

Employer

About Intuit

Intuit is a financial software company known for products like TurboTax, QuickBooks, Mint, and Credit Karma, helping consumers and small businesses manage their finances and taxes. Industry: Financial Software & Technology

Intuit currently has 199 open roles on FindRole.

Listed pay typically runs $202,500–$274,000 across 180 roles with salary data.

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At a glance

TL;DR · Senior Staff Data Scientist, Lending

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Sr. Staff Data Scientist, Lending joins the Lending Data Science team to serve as an analytical leader and strategic thought partner for the QuickBooks Capital portfolio. This role involves translating business strategy into complex analytical problems, building reusable frameworks, and influencing senior leadership across product, marketing, and engineering functions. The successful candidate will advance scientific standards by identifying new machine learning and causal inference methodologies, leading large-scale experimentation including A/B testing and quasi-experimental designs, and developing durable customer segmentation strategies. Key responsibilities include shaping the AI-native roadmap and making build-versus-buy tooling decisions. Required skills include advanced SQL, Python or R proficiency, Tableau experience, and expertise in predictive modeling and generative AI workflows. The role addresses critical fintech challenges such as underwriting, credit risk, and LTV modeling to improve how small businesses manage cash flow.

What does a Data Scientist earn in California?

Median $213878 from 88 postings across 32 companies.

See salary data

Skills

Causal Inference Machine Learning Python R SQL Tableau A/B Testing Generative AI Experimental Design Statistics Prescriptive Modeling Customer Segmentation

What you'll do

Translate business strategy into actionable analytical problems and hypotheses across multiple lending initiatives.
Influence senior cross-functional leadership by providing insights grounded in deep customer understanding and industry context.
Develop and share advanced machine learning and causal inference frameworks for adoption across the business unit.
Design and execute complex experiments, including A/B testing and quasi-experimental designs where traditional testing is limited.
Create durable customer segmentation strategies to improve targeting, positioning, and user experience.
Co-create the AI-native roadmap by aligning model performance with safety, risk, and business outcomes.
Advise on build-versus-buy decisions and champion scalable tools to streamline analytics workflows.
Mentor data scientists and establish scientific standards and best practices across the team.

What we're looking for

9+ years of experience in data science and analytics with a track record of driving strategy across multiple initiatives.
Experience in fintech (lending, credit cards, or marketplaces) is preferred.
Proven ability to translate ambiguous business strategies into analytical problems using first-principles thinking.
Expertise in predictive/prescriptive modeling, causal inference, customer segmentation, and complex experimentation design.
Ability to create reusable frameworks, methodologies, and toolkits for adoption by a broader analytics community.
Exceptional communication skills with the ability to influence Director- and VP-level leaders across cross-functional teams.
Advanced SQL proficiency and experience with visualization tools like Tableau.
Proficiency in Python or R, including data workflow management and architecting generative AI workflows.
BS or MS in Statistics, Mathematics, Operations Research, Computer Science, Engineering, Econometrics, or a related field (advanced degree preferred).

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