Senior Data Scientist, Growth Analytics

Menlo Park · New York · Menlo Park - · New York - · 4+ years experience · Posted Sep 30, 2026

At a glance

Moloco builds some of the most powerful AI advertising solutions in the world. Our name—short for "machine learning company"—reflects our core mission: democratizing access to the advanced AI that has historically been reserved for tech giants. Led by machine learning pioneers who built some of the most successful ad systems at Google, including YouTube's monetization engine and key search advertising technologies, we're transforming how businesses grow and compete in the digital economy.
Built with AI from day one, Moloco’s planet-scale machine learning platform powers a suite of solutions for advertising growth and monetization. Moloco Ads is an AI-powered platform that delivers real business outcomes for mobile app marketers through performance-based user acquisition. Moloco Commerce Media enables retailers and marketplaces to build revenue-generating ad businesses that balance user experience and advertiser performance.
Moloco is headquartered in Silicon Valley, with offices in Seattle, New York, San Francisco, Seoul, Beijing, Singapore, Gurgaon, Tokyo, Shanghai, London, Tel Aviv, and Berlin.
Moloco is a truly rewarding place to work and in an exciting period of growth, which you could be a part of. Join us today and apply now!

The Growth Data Science team partners with advertisers, sales, product, and engineering to maximize the effectiveness of Moloco Ads.
This senior role serves as a bridge between advertiser commercial objectives and the technical direction of the product.
The position focuses on driving performant product activation for top-tier advertisers while synthesizing customer signals into product roadmap priorities.

Partner with top-tier advertisers to advise on campaign structure, measurement, bidding strategy, and optimization levers.
Translate account insights into structured product and GTM feedback for the roadmap.
Build and scale activation frameworks and playbooks for global GDS teams.
Serve as a senior technical voice in product conversations to influence roadmap decisions.
Systematically collect and synthesize customer feedback and market signals.
Define success metrics, design experiments, and evaluate new product features.
Translate complex advertiser problems into clear product requirements and value propositions.
Define and own the global GDS approach to product activation.
Act as a thought leader within GDS to set standards for analytical rigor and stakeholder communication.
Collaborate across AMER, EMEA, and APAC teams to ensure consistency in product market entry.

Bachelor's degree in a quantitative discipline (Statistics, Computer Science, Economics, Mathematics, Physics, or equivalent).
4+ years in data science, analytics, or a closely related quantitative field.
Significant experience in a customer-facing or product-facing individual contributor capacity.
Strong foundation in experimental design, hypothesis testing, regression, and causal inference methods.
Proficiency in Python and SQL.
Exceptional verbal and written communication skills with the ability to distill technical concepts for C-level audiences.
Demonstrated ability to build and maintain credibility with cross-functional partners.
Proven ability to own projects end-to-end in ambiguous problem spaces.
Demonstrated self-direction and senior-level judgment.

Graduate degree (Master's or PhD) in a quantitative discipline.
Prior experience in ad tech, programmatic advertising, DSP/SSP, or performance marketing.
Familiarity with mobile app ecosystems and MMP measurement frameworks.
Experience working with or at a mobile app advertiser (gaming, fintech, social) with exposure to UA strategy, LTV optimization, or monetization.
Hands-on experience shaping product roadmaps as a data scientist.
Track record of building scalable frameworks, playbooks, or methodologies adopted by a wider team.
Familiarity with incrementality testing methodologies (geo holdouts, ghost bidding, PSA tests).
Experience with large-scale data platforms like BigQuery.