Lead Data Scientist, AdTech

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $175k - $200k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 19%

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Launch Potato

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2015

📣 Marketing

📱 Media

👥 B2C

Marketing • Media • B2C

Launch Potato is South Florida's fastest growing digital media company, founded by a group of young and ambitious individuals with a history of building successful direct-to-consumer digital businesses. Headquartered in Delray Beach, FL, Launch Potato operates with a distributed global team. The company focuses on solving complex problems with smart marketing, great engineering, data science, and fun, emphasizing its commitment to innovation and scalability.

📋 Description

• Build models deciding which auto insurance carrier each shopper sees on the click wall • Optimize user-to-carrier matching for conversion and carrier bidding • Own buying models behind media spend and hold them to ROAS • Put carrier conversion data, including quotes, policies and acquisition cost, into production models • Frame problems with the business and find, build and validate models • Take models through deployment and monitoring • Run insurance marketplace media buying independently by day 60 • Deliver click-wall matching, production conversion models, scalable automated bidding, approaches for repeat users and sparse sessions, and models resilient to drift and changing objectives • Collaborate with an ML engineer on production implementation • Expand scope from auto insurance to other verticals over time

🎯 Requirements

• 5+ years of hands-on applied data science with measurable business impact • Models drove paid media decisions: spend, bidding or ad serving; attribution and reporting alone do not qualify • Ability to explain work down to the loss function and architecture choice, including neural network fundamentals • Experience handling late labels, sparse features or drift • Ability to own models end to end, from finding data through deployment and monitoring • Expert Python and SQL • Real ad budget spent in live auctions (nice to have) • Large-scale ranking or recommendation systems (nice to have) • Explaining tradeoffs to non-technical partners (nice to have) • Designing for auction feedback loops, selection bias and exploration (nice to have) • Hands-on neural network work (nice to have) • AWS for data science: ECS, S3, Athena, SageMaker (nice to have) • CI/CD deployment (nice to have)

🏖️ Benefits

• Profit-sharing bonus • Competitive benefits • Remote-first work arrangement • Diverse, inclusive team and culture • Equal Employment Opportunity company