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Launch Potato

Staff Applied Scientist, AdTech

RemotePanama, United States only
Published
Role
Data Science
Experience
Staff
Salary not disclosed
Check eligibility

Open to PA, US only. Set where you work from to check your eligibility.

No BS summary

Staff-level applied data scientist for AdTech/performance marketing with 5+ years hands-on experience. Must have strong modeling fundamentals, AWS ML deployment experience, Python and SQL, and work with user acquisition or paid media modeling. Remote role tied to Panama City, Panama.

Core skills

PythonSQLMachine Learning

Required skills

AWSMulti-armed banditReinforcement LearningRecommendation SystemsRanking SystemsLTV Modeling

Optional skills

EmbeddingsAd Ranking AlgorithmsGoogle AdsMeta AdsNative AdvertisingLLMsDeep LearningLooker

What you'll do

  • 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 an ML engineering partner.
  • Stay engaged through deployment, monitoring, and performance analysis.
  • Start focusing on Insurance and Advertiser Quality, with scope that broadens over time.
  • 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 the 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.

What they require

  • Proven experience in digital marketing, performance marketing, or the leadgen industry.
  • Building adtech algorithms and supporting user acquisition or paid media modeling is 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.
  • 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.
  • Preferred: Sophisticated ML at companies where paid digital media is core to the business model.
  • Preferred: Insurance domain experience.

Benefits

  • You own outcomes here, not tasks.
  • We measure work by impact, not activity.
  • Feedback runs direct and lands with respect.
  • Remote-first team across 18 countries.
🇺🇸 United StatesDigital MediaStartup

Details

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Salary not disclosed