Senior Data Scientist, AdTech & Media Bidding

Launch Potato; Phoenix (AZ); A distancia; USD 175.000 - 200.000; Jornada completa

Descripción de la vacante

Launch Potato, a remote-first discovery and conversion company, is seeking an experienced data scientist to build models that decide which auto insurance carrier a shopper sees on our click wall. You will own the buying models behind media spend and ROAS, turning data into actionable production insights and measurable outcomes.

You’ll frame problems with the business, find and prepare data, validate models, and partner with an ML engineer on deployment and monitoring.

Formación

• 5+ years of hands-on applied data science with measurable business impact.
• Your models drove paid media decisions: spend, bidding or ad serving. Attribution and reporting alone don't qualify.
• You built what's on your resume and can explain it down to the loss function and architecture choice.
• You understand how bids shape training data, handle late labels, sparse features or drift.
• You own models end to end from data discovery to deployment and monitoring.
• Expert Python and SQL.

Responsabilidades

• Build models that decide which auto insurance carrier a shopper sees on our click wall.
• Own the buying models behind media spend and ROAS; production deployment.
• Frame business problems, find data, validate models, and monitor performance.
• Collaborate with an ML engineer on the production side; start with auto insurance, expand later.

Conocimientos

Python

SQL

Data science

Model deployment

Drift handling

Neural networks

Herramientas

AWS

SageMaker

ECS

S3

Athena

CI/CD

Descripción del empleo

Launch Potato, a remote-first discovery and conversion company, is seeking an experienced data scientist to build models that decide which auto insurance carrier a shopper sees on our click wall. You will own the buying models behind media spend and ROAS, turning data into actionable production insights and measurable outcomes.

You’ll frame problems with the business, find and prepare data, validate models, and partner with an ML engineer on deployment and monitoring.