Staff Data Scientist, Marketing

Launch Potato is a profitable digital media company that reaches over 30M+ monthly visitors through brands such as FinanceBuzz, All About Cookies, and OnlyInYourState. The company is headquartered in South Florida with a remote-first team spanning over 15 countries, focusing on connecting consumers with leading brands through data-driven content and technology.

Location: Canada

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.
• Start focusing on Insurance and Advertiser Quality, with scope that broadens over time.
• 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 the 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.

Requirements

• 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.

Additional Information

• The role is hands-on and involves deep immersion in data and modeling.
• Primary metric is ROAS.
• The role involves collaboration with ML engineering teams for deployment and performance monitoring.
• The company values diversity, equity, and inclusion.