Staff Applied Scientist – AdTech

Launch Potato

Staff Applied Scientist responsible for end-to-end data science engine focusing on insurance vertical. Driving revenue efficiency and collaborating with stakeholders at Launch Potato.

Posted 7/1/2026full-timeRemote • 🇺🇸 United StatesLeadWebsite

Tech Stack

Tools & technologies

AWSCloudPythonSQL

About the role

Key responsibilities & impact

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
This is a hands-on, in-the-weeds role: you are heavily immersed in the data and the modeling, framing the business problem directly with stakeholders, building and validating the model, handing the ML-engineering last mile to your ML engineering partner, and staying engaged through deployment, monitoring, and performance analysis
You will start focusing on Insurance and Advertiser Quality, with scope that broadens over time
Your primary metric is ROAS
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

Requirements

What you’ll need

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

Benefits

Comp & perks

Base salary is set according to market rates for the nearest major metro
Profit-sharing bonus
Competitive benefits
Performance-driven company: future increases based on company and personal performance, not annual cost of living adjustments

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Modeling FundamentalsMulti-Armed BanditReinforcement LearningRecommendation SystemsFunnel OptimizationLTV Modeling

Soft Skills

Stakeholder EngagementPartnership Building