[Remote] Staff Applied Scientist, AdTech

Note: The job is a remote job and is open to candidates in USA. Launch Potato is a profitable digital media company that connects consumers with leading brands through data-driven content and technology. The Staff Applied Scientist will own the data science engine for a priority vertical, focusing on modeling and performance analysis to drive measurable revenue and media efficiency.

Responsibilities

• Own the full data science engine for a priority vertical, from business problem to deployed model to live ROAS performance, driving measurable revenue and media efficiency
• Own the Insurance vertical's primary modeling work end-to-end with measurable ROAS impact
• Deliver buying models that maintain positive ROAS and quality
• Drive lead quality improvements across our portfolio of brands: Messaging, Funnels, Content/Listicles, and more resulting in measurable impact to revenue growth
• Establish trusted, direct partnership with vertical business stakeholders
• Produce trusted output: validated, documented, low correction burden
• Identify and leverage net-new modeling opportunities the business has not flagged

Skills

• Proven experience in digital marketing, performance marketing, or the leadgen industry
• Building adtech algorithms and supporting user acquisition or paid media modeling (highly desired)
• 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
• 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

Benefits

• Profit-sharing bonus
• Competitive benefits

Company Overview