Jobs · Engineering

Lead Data Scientist, AdTech

Launch Potato · Phoenix, AZ · 1 wk ago
RemoteRemoteEngineering$175k–$200k/yrFull-time

WHO ARE WE?

Launch Potato is a profitable digital media company reaching over 30M+ monthly visitors through brands like FinanceBuzz, All About Cookies, and OnlyInYourState. Our mission is to connect consumers with leading brands through data-driven content and technology. Headquartered in South Florida with a remote-first team spanning 15+ countries, we foster a high-growth, high-performance culture where speed, ownership, and measurable impact drive success.

WHY JOIN US?

At Launch Potato, you'll accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers. Base salary ranges from $175,000 to $200,000 per year, paid semi-monthly.

MUST HAVE:

  • 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

EXPERIENCE:

5+ years in a hands-on, in-the-weeds applied data science role delivering measurable business impact.

YOUR ROLE

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.

YOUR PRIMARY VERTICAL:

Insurance and Advertiser Quality, with scope that broadens over time. Your primary metric is ROAS.

OUTCOMES

  • 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

CERTIFICATIONS AND SKILLS

  • Business-first framing: Starts with the problem and the metric, not the model.
  • Full-stack ownership: Stays engaged from problem definition through deployed performance
  • Proactive communication: Closes loops without being chased
  • Collaborative: Leans on ML engineering for the last mile rather than working solo
  • Coachable: Seeks feedback and turns it into visible behavior change
  • Curiosity paired with delivery discipline

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

TOTAL COMPENSATION

Your compensation package includes a base salary, profit-sharing bonus, and competitive benefits. Launch Potato is a performance-driven company, which means future increases will be based on company and personal performance, not annual cost of living adjustments.

COMPETENCIES

  • Business-first framing: Starts with the problem and the metric, not the model.
  • Full-stack ownership: Stays engaged from problem definition through deployed performance
  • Proactive communication: Closes loops without being chased
  • Collaborative: Leans on ML engineering for the last mile rather than working solo
  • Coachable: Seeks feedback and turns it into visible behavior change
  • Curiosity paired with delivery discipline

APPLICATION

To apply, please visit our careers page and submit your application.

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