Lead Applied Scientist, Marketing
RemoteValparaíso, Valparaíso, Chile
Job Summary
Own the full data science engine for the Insurance vertical, from business problem framing to deployed model and live ROAS performance. Build and validate buying models that maintain positive ROAS and drive lead quality improvements across Messaging, Funnels, Content/Listicles, and other portfolio brands. Collaborate with ML engineering partners to deploy the last mile of solutions while monitoring performance and analyzing metrics daily. Establish trusted partnerships with vertical stakeholders to close loops without being chased. Focus on multi-armed bandit, reinforcement learning, and ranking systems to optimize monetization and LTV. Apply sophisticated ML techniques including creative embeddings and LLMs to personalization, leveraging AWS cloud infrastructure. Drive measurable revenue growth and media efficiency through proactive communication and delivery discipline.
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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