Launch Potato

Launch Potato

Launch Potato is a South Florida-based startup studio that connects the world's fastest growing brands to customers across the consumer journey. Founded by ambitious individuals, they leverage data, science, and fun to build successful digital companie...

Professional Services
51-250
Founded 2014

Description

  • Own the full data science workflow from business problem definition through deployed model performance for a priority vertical.
  • Partner directly with business stakeholders to frame problems around measurable metrics and outcomes.
  • Build, validate, and document models that improve ROAS, lead quality, revenue growth, and media efficiency.
  • Hand off the ML engineering last mile to an ML engineering partner while remaining engaged through deployment and monitoring.
  • Monitor live model performance and analyze results after deployment.
  • Identify new modeling opportunities not already flagged by the business.
  • Develop solutions for Insurance and Advertiser Quality initially, with scope expanding over time.
  • Improve lead quality across brands, funnels, content, and messaging initiatives.

Requirements

  • 5+ years of hands-on applied data science experience delivering measurable business impact.
  • Proven experience in digital marketing, performance marketing, or the lead generation industry.
  • Highly desired: experience building adtech algorithms and supporting user acquisition or paid media modeling.
  • Multi-year, hands-on experience building and deploying ML solutions in AWS.
  • Strong modeling fundamentals and the ability to build effective models that drive business impact.
  • Hands-on experience with multi-armed bandits or reinforcement learning.
  • Hands-on experience with recommendation and ranking systems, including content-based, collaborative filtering, and hybrid approaches.
  • Hands-on experience with funnel and monetization optimization and LTV modeling.
  • Expert-level Python and SQL skills.
  • Nice to have: experience with sophisticated ML in companies where paid digital media is core to the business.
  • Nice to have: creative embeddings work using creatives, videos, headlines, and search in paid media models.
  • Nice to have: insurance domain experience.
  • Nice to have: experience creating state-of-the-art ad ranking algorithms.
  • Nice to have: modeling against ad-platform data from Google, Meta, or native platforms.
  • Nice to have: experience using LLMs or deep learning for personalization or content.
  • Nice to have: familiarity with Looker.

Benefits

  • Base salary of $175,000 to $200,000 per year, paid semi-monthly.
  • Total compensation includes base salary, profit-sharing bonus, and competitive benefits.
  • Remote-first work environment with a team spanning over 15 countries.
  • Performance-based future increases tied to company and personal performance.
  • Opportunity to work in a high-growth, high-performance culture focused on ownership and impact.

Interested in this position?

Apply directly on the company website

Apply Now

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