Senior Data Scientist, Growth Analytics

Description

The company is an AI-native performance advertising company that runs two businesses on one shared AI system: an ad platform that helps mobile app marketers acquire, retain, and re-engage high-value users, and a retail media platform that helps retailers and marketplaces build ad businesses.

You will join Growth Data Science, the global data science team that works with advertisers, sales, product, and engineering to make the ad platform perform better.

This is a newly created senior role. The company needs a technically strong senior data scientist who can drive results for its largest advertisers and turn what those customers report into product priorities.

You will sit between customer-facing data science and product strategy, working daily with product, engineering, sales, and go-to-market teams so that what gets built is activated well and what advertisers need informs the next builds.

Across the AMER, EMEA, and APAC teams, you will set up repeatable frameworks and playbooks that the wider team can use, not just work on one account at a time.

Responsibilities

• Work directly with the company's largest advertisers to get the most from the product suite, advising on campaign structure, measurement, bidding, and optimization levers.
• Turn account-level findings into product roadmap signals and send structured product and go-to-market feedback to the right teams.
• Set the bar for how Growth Data Science engages advertisers, so other team members can follow your approach.
• Build activation frameworks that regional teams can run across their accounts, moving the team from ad hoc work to a repeatable model.
• Speak for Growth Data Science in product discussions, using advertiser insight and analysis to shape roadmap decisions.
• Gather, analyze, and communicate customer feedback and market signals to product and engineering so the roadmap reflects real advertiser needs.
• With product data scientists and engineers, define success metrics, design experiments, and assess new features before and after launch.
• Convert complex, unclear advertiser problems into clear product requirements and value propositions that both commercial and technical teams can act on.
• Own the global approach to product activation, including the frameworks, tools, and best practices that raise the impact of the whole team.
• Lead by example within Growth Data Science on analytical rigor, stakeholder communication, and cross-functional influence.
• Coordinate with the AMER, EMEA, and APAC teams to keep how the product reaches market and how customer insight returns to the business consistent.

Requirements

• Bachelor's degree in a quantitative field such as Statistics, Computer Science, Economics, Mathematics, or Physics, or equivalent practical experience.
• 4+ years in data science, analytics, or a closely related quantitative field, with substantial time in a customer-facing or product-facing individual contributor role.
• Solid grounding in experimental design, hypothesis testing, regression, and causal inference.
• Python and SQL are required. Experience with large-scale data platforms such as BigQuery is preferred.
• Able to explain complex technical ideas to non-technical audiences, up to C-level, in speech and writing.
• Has built and kept credibility with product, engineering, sales, and go-to-market partners.
• Has taken ownership of ambiguous projects from start to finish and delivered measurable results.
• Works independently with senior-level judgment, and can build a process when none exists.
• Preferred: Master's or PhD in a quantitative discipline.
• Preferred: Background in ad tech, programmatic advertising, DSP/SSP, or performance marketing, with good familiarity with mobile app ecosystems and MMP measurement frameworks.
• Preferred: Experience working with or at a mobile app advertiser in gaming, fintech, or social, with direct exposure to user acquisition strategy, LTV optimization, or monetization.
• Preferred: Hands-on experience shaping a product roadmap as a data scientist, actively influencing what gets built and why, not only evaluating features.
• Preferred: Track record of building scalable frameworks, playbooks, or methods that a wider team has adopted.
• Preferred: Familiarity with incrementality testing methods such as geo holdouts, ghost bidding, and PSA tests, and how to apply them with advertisers.

Conditions

U.S.-based employees get medical, dental, and vision insurance, a 401(k) with company match, short-term and long-term disability coverage, basic life insurance, and well-being benefits. They also receive up to 12 scheduled paid holidays per calendar year, one Thrive Day off per quarter, and Flexible Time Off.

The successful candidate may be eligible for a bonus and equity awards, based on performance and the terms of the applicable plans.

Base pay depends on work location, grouped into three U.S. regions. Region A (Menlo Park Office, New York Office, SF Bay Area, New York Metro Area): $180,000 - $225,000 USD. Region B (Seattle Office, Seattle, Los Angeles/Orange County, San Diego, Austin, Boston, Washington DC Metro Area, Miami): $162,000 - $202,500 USD. Region C (all other U.S. locations): $153,000 - $191,250 USD.

Benefits vary by country, employment type, and eligibility. A recruiter can explain what applies in your region.

The company is an equal opportunity employer.

Benefits

• Medical, dental, and vision insurance for U.S.-based employees.
• 401(k) plan with company match for U.S.-based employees.
• Short-term and long-term disability coverage and basic life insurance for U.S.-based employees.
• Well-being benefits and perks for U.S.-based employees.
• Up to 12 scheduled paid holidays per calendar year and one Thrive Day off per quarter for U.S.-based employees.
• Flexible Time Off for all employees.
• Possible bonus and equity awards.