Staff Applied Scientist, AdTech
RemoteBuenos Aires, Buenos Aires F.D., Argentina
Job Summary
Own the full data science engine for the Insurance vertical, framing business problems directly with stakeholders to build and validate models that drive measurable ROAS. Deliver buying models maintaining positive ROAS and lead quality across Messaging, Funnels, Content/Listicles, and other portfolio brands. Stay engaged from problem definition through deployed performance, handing the last mile to ML engineering while monitoring live results. Focus on advertiser quality and net-new modeling opportunities, producing validated, documented outputs with low correction burden. This hands-on role requires 5+ years of applied data science experience, with a strong emphasis on Python, SQL, and multi-armed bandit algorithms.
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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