Lead Data Scientist, AdTech

Launch Potato•St. Louis, MO

4d•$175,000 - $200,000•Remote

About The Position

Launch Potato is a profitable digital media company that reaches over 30M+ monthly visitors. As The Discovery and Conversion Company, our mission is to connect consumers with the world’s leading brands through data-driven content and technology. Headquartered in South Florida with a remote-first team spanning over 15 countries, we’ve built a high-growth, high-performance culture where speed, ownership, and measurable impact drive success. At Launch Potato, you’ll accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers. This role will start focusing on Insurance and Advertiser Quality, with scope that broadens over time. Your primary metric is ROAS.

Requirements

Proven experience in digital marketing, performance marketing, or the leadgen industry
Building adtech algorithms and supporting user acquisition or paid media modeling (highly desired)
Strong modeling fundamentals: the ability to build effective models that drive business impact
Multi-year, hands-on experience building and deploying ML solutions in the AWS cloud
Hands-on experience across core technique areas: multi-armed bandit / reinforcement learning, recommendation and ranking systems (content-based, collaborative filtering, hybrid), funnel and monetization optimization, LTV modeling
Expert Python and SQL
5+ years in a hands-on, in-the-weeds applied data science role delivering measurable business impact.

Nice To Haves

Sophisticated ML at companies where paid digital media is core to the business model
Creative embeddings work: incorporating embeddings of creatives, videos, headlines, and search into paid media models
Insurance domain experience
Creating state-of-the-art Ad Ranking algorithms
Modeling against ad-platform data points (Google, Meta, native)
LLMs / deep learning applied to personalization or content
Familiarity with Looker

Responsibilities

Own the full data science engine for a priority vertical, from business problem to deployed model to live ROAS performance, driving measurable revenue and media efficiency.
Frame the business problem directly with stakeholders, build and validate the model, hand the ML-engineering last mile to your ML engineering partner, and stay engaged through deployment, monitoring, and performance analysis.
Own the Insurance vertical's primary modeling work end-to-end with measurable ROAS impact.
Deliver buying models that maintain positive ROAS and quality.
Drive lead quality improvements across our portfolio of brands: Messaging, Funnels, Content/Listicles, and more resulting in measurable impact to revenue growth.
Establish trusted, direct partnership with vertical business stakeholders.
Produce trusted output: validated, documented, low correction burden.
Identify and leverage net-new modeling opportunities the business has not flagged.