Staff Applied Scientist – AdTech

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of the complete data science engine for a key vertical, from identifying business challenges to deploying models and analyzing live ROAS performance, ultimately driving measurable revenue and media efficiency.

• This role is hands-on and detail-oriented: you will be deeply involved in the data and modeling processes, collaborating closely with stakeholders to define business problems, building and validating models, coordinating the final stages with your ML engineering partner, and remaining engaged throughout deployment, monitoring, and performance evaluation.

• Initially, you will concentrate on Insurance and Advertiser Quality, with an opportunity for broader responsibilities over time.

• Your main performance indicator will be ROAS.

• Take charge of the primary modeling efforts within the Insurance vertical, ensuring measurable ROAS outcomes.

• Create purchasing models that sustain positive ROAS and uphold quality standards.

• Enhance lead quality across our diverse portfolio of brands, including Messaging, Funnels, and Content/Listicles, leading to a tangible impact on revenue growth.

• Establish a trusted, direct relationship with business stakeholders in the vertical.

• Deliver reliable outputs: validated, documented, and with minimal correction requirements.

• Discover and utilize new modeling opportunities that the business has yet to recognize.

⛳️ Requirements

• Demonstrated experience in digital marketing, performance marketing, or the lead generation industry.

• Experience in developing adtech algorithms and facilitating user acquisition or paid media modeling is highly preferred.

• Strong foundational skills in modeling: the capability to create impactful models that influence business outcomes.

• Several years of hands-on experience in building and deploying machine learning solutions within the AWS cloud environment.

• Practical experience across essential technique areas: multi-armed bandit/reinforcement learning, recommendation and ranking systems (content-based, collaborative filtering, hybrid), funnel optimization, monetization strategies, and LTV modeling.

• Proficient in Python and SQL.

• At least 5 years in a hands-on, applied data science position delivering significant business results.

🏝️ Benefits

• Base salary is aligned with market rates for the closest major metropolitan area.

• Profit-sharing bonus.

• Competitive benefits package.

• Performance-oriented company: future salary increases are based on both company and individual performance rather than annual cost of living adjustments.