Remote Senior Applied Scientist, AdTech & ROAS

Socket.dev; Arlington (VA); On-site; USD 175,000 - 200,000; Full time

Job summary

Launch Potato is seeking a data science leader to own the full data science engine for a priority vertical, driving ROAS through deployed models and media efficiency. You will work closely with stakeholders and an ML engineering partner, staying engaged through deployment, monitoring, and performance analysis.

Initial focus on Insurance and Advertiser Quality with expansion over time, leveraging strong modeling, Python/SQL skills, and AWS ML capabilities to impact revenue.

Qualifications

• 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, funnel and monetization optimization, LTV modeling
• Expert Python and SQL

Responsibilities

• Own the full data science engine for a priority vertical, from business problem to deployed model to live ROAS performance.
• This is a hands-on role: you will be heavily immersed in the data and the modeling, framing the business problem with stakeholders, building and validating the model, and handing the ML-engineering last mile to an ML engineering partner.
• You will start focusing on Insurance and Advertiser Quality, with scope broadening over time; primary metric is ROAS.

Skills

Python

SQL

ML

Tools

AWS

Job description

Launch Potato is seeking a data science leader to own the full data science engine for a priority vertical, driving ROAS through deployed models and media efficiency. You will work closely with stakeholders and an ML engineering partner, staying engaged through deployment, monitoring, and performance analysis.

Initial focus on Insurance and Advertiser Quality with expansion over time, leveraging strong modeling, Python/SQL skills, and AWS ML capabilities to impact revenue.