Staff Applied Scientist, AdTech
RemoteAntigua and Barbuda or South, Kentucky, United States
Job Summary
Own the full data science engine for the Insurance vertical, from business problem definition to deployed model and live ROAS performance. Build and validate buying models that maintain positive ROAS and lead quality across Messaging, Funnels, Content/Listicles, and other portfolio brands. Frame problems directly with stakeholders, hand ML-engineering the last mile to your partner, and stay engaged through deployment, monitoring, and performance analysis. Deliver validated, documented outputs with low correction burden while identifying net-new modeling opportunities. Focus on multi-armed bandit, reinforcement learning, and ranking systems using Python and SQL in AWS.
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
- 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
Desired Qualifications
- Building adtech algorithms and supporting user acquisition or paid media modeling (highly desired)
- 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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