Staff Applied Scientist, AdTech
RemoteValparaíso, Valparaíso, Chile
Valparaíso, Valparaíso, ChileRemoteFull TimeSenior LevelDoctorate Or Professional DegreeDigital MediaSmall
Full TimeSenior LevelDoctorate Or Professional DegreeSmallDigital Media
Job Summary
Own the full data science engine for the Insurance vertical, framing business problems to drive ROAS and lead quality improvements across messaging, funnels, and content. Build and deploy ML solutions in AWS for buying models, recommendation systems, and monetization optimization, partnering with engineering teams for the last mile. Deliver validated outputs with low correction burdens while identifying net-new modeling opportunities to maintain positive ROAS. Focus on advertiser quality and insurance domain challenges, leveraging Python, SQL, and reinforcement learning to maximize media efficiency and revenue growth.
Required Qualifications
- Proven experience in digital marketing, performance marketing, or the leadgen industry
- Multi-year, hands-on experience building and deploying ML solutions in the AWS cloud
- Expert Python and SQL
- 5+ years in a hands-on, in-the-weeds applied data science role delivering measurable business impact
Desired Qualifications
- Building adtech algorithms and supporting user acquisition or paid media modeling
- Strong modeling fundamentals: the ability to build effective models that drive business impact
- 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
- 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
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