Lead Data Scientist, AdTech

About the company

The organization operates in the digital advertising and customer acquisition space, focusing on connecting discovery, intent, and performance across consumer brands in finance, travel, and entertainment. It addresses the challenge of turning large-scale audience attention into predictable, high-value customer acquisition for partner companies through data-driven marketing solutions. The company maintains a remote-first team distributed across multiple countries with headquarters in South Florida.

About the role

The LEAD DATA SCIENTIST, ADTECH is responsible for developing and managing predictive models that determine which auto insurance carrier is presented to each shopper, aiming to maximize conversion rates and optimize bidding strategies for media spend. This role directly influences revenue by improving marketplace efficiency and conversion outcomes through data-driven decision making. The position requires hands-on involvement from problem framing through to model deployment and ongoing performance monitoring, with an initial focus on auto insurance and potential expansion into other verticals.

Responsibilities

• Build and validate models to select the most likely converting insurance carrier for each user
• Develop buying models to optimize media spend and maintain return on ad spend (ROAS)
• Integrate carrier conversion data into production models
• Address challenges with delayed outcomes, sparse session data, repeat users, and market drift
• Collaborate with ML engineers for production deployment
• Independently manage the entire modeling lifecycle from data acquisition to monitoring
• Expand modeling efforts to additional verticals over time

Requirements

• Minimum 5 years of applied data science experience with measurable business impact
• Proven experience developing models that directly influence paid media decisions such as spend and bidding
• Deep understanding of model design including loss functions, neural network fundamentals, and architecture choices
• Experience handling feedback loops where bids influence future training data, late label problems, sparse features, and market drift
• Ownership of end-to-end modeling processes including data sourcing, model building, deployment, and monitoring
• Proficiency in Python and SQL

Pay

Base salary range of $175,000 to $200,000 per year, paid semi-monthly.