Senior Data Scientist, AdTech — Optimize Bids & Carrier Matches

Launch Potato; Austin, Dallas, Oklahoma City (TX, TX, OK); Ibrido; USD 175.000 - 200.000; Tempo pieno

Vantaggi offerti da questo lavoro

Profit-sharing bonus

Competitive benefits

Descrizione del lavoro

Launch Potato is seeking an experienced data scientist to build end‑to‑end models guiding which carrier a shopper sees on our insurance marketplace. You will own data gathering, modeling, deployment, and monitoring, with production-ready pipelines and collaboration with an ML engineer.

The role emphasizes solving real business problems, handling sparse data, and maintaining model performance in a dynamic bidding environment. Remote-first team across time zones.

Competenze

• 5+ years of hands-on applied data science with measurable business impact.
• Built models that informed paid media decisions: spend, bidding or ad serving.
• Explain model choices down to loss function and architecture.
• Handled late labels, sparse features or drift in production models.
• Own models end to end from data gathering to deployment and monitoring.
• Expert Python and SQL.

Mansioni

• Build and validate production models for insurance marketplace media buying.
• Frame problems with business context and run end-to-end from data to deployment.
• Collaborate with an ML engineer on production integration.
• Improve models to adapt to drift and changing objectives.
• Deliver outputs that drive business value and ROAS.

Conoscenze

Python

SQL

Data science

Machine learning

Strumenti

AWS

SageMaker

ECS

S3

Athena

Descrizione del lavoro

Launch Potato is seeking an experienced data scientist to build end‑to‑end models guiding which carrier a shopper sees on our insurance marketplace. You will own data gathering, modeling, deployment, and monitoring, with production-ready pipelines and collaboration with an ML engineer.

The role emphasizes solving real business problems, handling sparse data, and maintaining model performance in a dynamic bidding environment. Remote-first team across time zones.