Staff Data Scientist (Marketing)

TL;DR

Staff Data Scientist (Marketing): Building the marketing data science function from the ground up to measure success and optimize channel performance with an accent on attribution modeling and growth analytics. Focus on designing scalable dashboards, implementing MMM and incrementality models, and optimizing user behavior forecasting.

Location: San Francisco, USA

Salary: $170,000 – $260,000 USD

Company

Transforming legal and professional services by combining frontier agentic AI with an enterprise-grade platform.

What you will do

• Partner with Marketing, GTM, and Finance to define, track, and evolve core success metrics.
• Build scalable dashboards and reporting frameworks to enable data-driven decision-making across the business.
• Design and implement complex models, including multi-touch attribution, marketing mix modeling (MMM), and incrementality.
• Apply statistical and machine learning techniques to model user behavior and forecast growth trends.
• Collaborate with RevOps and GTM Systems to co-develop robust data infrastructure and reliable pipelines.
• Lead cross-functional analytics initiatives that translate market trends and customer feedback into actionable opportunities.

Requirements

• 6+ years of experience in quantitative roles, ideally within hyper-growth product companies or research organizations.
• Expertise in SQL, including extracting large datasets and designing ETL workflows.
• Hands-on experience working with Salesforce, Marketo, and Ads spend data.
• Proficiency with modern data stack tools such as DBT, Looker, and Omni.
• Strong proficiency in quantitative programming languages like Python or R.
• Ability to effectively partner with and deliver recommendations to cross-functional executives.

Culture & Benefits

• High-intensity environment emphasizing ownership, decisiveness, and professional excellence.
• Competitive compensation package including equity offers.
• Opportunity to join a generational company at a scaling inflection point.
• Culture based on simplicity, speed of execution, and a "Job's Not Finished" mindset.