Senior Data Scientist - Mid-Market Product

Position: Senior Staff Data Scientist - Mid-Market Product Growth
Company Overview Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With tens of millions of customers worldwide using products such as Turbo Tax, Credit Karma, Quick Books, 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 Intuit Global Business Solutions Group (GBSG) Data Science has an exciting opportunity to be part of the fast-growing Mid-market Data Science team that plays a critical role in driving growth with a long-term winning strategy. Disrupting the small business mid-market is one of Intuit's 3 Big Bets initiatives. We are looking for a Senior Staff Data Scientist to serve as an analytical leader and strategic thought partner for our Mid-market Product Growth initiatives.

This is a high-impact individual contributor role where you will set the analytics and measurement vision, raise the scientific bar, and influence product and business strategy for the mid-market segment. You will partner closely with senior leaders across Product, Customer Success, Marketing, Engineering, and Design to identify the biggest growth opportunities across the end-to-end customer journey—from acquisition and activation to habit formation and long-term retention.

Intuit has embraced a hybrid working model and this role will be based out of our Mountain View office 3 days per week.

Responsibilities Influence Product Strategy:
Serve as a strategic thought partner to senior Product and Business leaders (up to EVP-level). Influence product strategy by conducting deep-dive analyses on customer segmentation, funnel optimization, product adoption, and voice of the customer.

Set the Analytics Vision:
Establish the measurement architecture, key success metrics, and leading indicators used to evaluate the health and growth of the Mid-market product ecosystem.

Lead Experimentation & Causal Measurement:
Drive an iterative experimentation culture by designing complex experiments (A/B/n, multi-armed bandits) and applying causal inference methodologies (e.g., Propensity Score Matching, Difference-in-Differences) where traditional A/B testing is limited.

Shape the AI-Native

Roadmap:

Develop ML models and LLM applications to address complex product problems. Partner with product and engineering teams to integrate intelligent personalization, lead scoring, and generative AI features into the customer experience.

Uncover Growth Opportunities:
Use first-principles thinking and data mining to proactively explore and identify new business opportunities across the funnel, quantifying potential impact to guide investment prioritization.

Raise the Scientific Bar & Mentorship:
Create reusable analytical frameworks, methodologies, and tools that improve decision-making ch, mentor, and elevate junior data scientists on the team while remaining hands-on with the highest-leverage problems.

Serve as a tech team lead and supervise a team of 3-5 senior to staff data scientist.

Qualifications

Experience:

8+ years of experience in data science, product analytics, or related fields, with a proven track record of driving strategy and measurable business impact. Experience in B2B SaaS or fintech is highly preferred.

Technical Mastery:
Highly proficient in AI-native data science tech stack (Claude/Cursor/Codex + MCPs/CLIs/APIs). Expert-level proficiency in SQL and Complext Data Modeling. Advanced practical experience applying machine learning (classification, regression, ranking) and LLMs / GenAI workflows to real-world product problems.

Experimentation Rigor:
Deep expertise in experimentation, causal inference, and advanced customer segmentation, with the judgment…