Lead Applied Scientist, Marketing
RemoteAlajuela, Alajuela Province, Costa Rica
Job Summary
Own the full data science engine for the Insurance vertical, from business problem framing to deployed model and live ROAS performance. Build buying models that maintain positive ROAS and lead quality across Messaging, Funnels, and Content/Listicles. Deliver validated, documented outputs with low correction burden while partnering directly with stakeholders. Leverage multi-armed bandit, reinforcement learning, and recommendation systems to drive revenue growth and media efficiency. Focus initially on Advertiser Quality, with scope broadening over time. Collaborate with ML engineering for the last mile and stay engaged through deployment and monitoring.
Required Qualifications
- Proven experience in digital marketing, performance marketing, or the leadgen industry
- 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
- 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 (highly desired)
- 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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