Staff Applied Scientist, AdTech
RemoteLa Ciudad, Estado de Durango, Mexico
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 return on ad spend and drive lead quality improvements across messaging, funnels, and content portfolios. Frame problems directly with stakeholders, hand off the last mile to ML engineering, and stay engaged through deployment monitoring and performance analysis. Focus on multi-armed bandit and reinforcement learning techniques to optimize monetization and LTV. You will deliver validated, documented outputs with low correction burdens while identifying net-new modeling opportunities. This role expands in scope over time as you establish trusted partnerships with vertical business stakeholders to accelerate revenue growth and media efficiency.
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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