Lead Data Scientist, AdTech - Optimize Media Bids

Launch Potato; Argentina; Híbrido; ARS 181.747.000 - 272.620.000; Tempo integral

Benefícios oferecidos por esta vaga

Remote-first

East Coast hours

Global team across 18 countries

Resumo da vaga

Launch Potato seeks an experienced data scientist to own end-to-end ML models for our auto insurance marketplace. You will build, validate, and deploy models that match shoppers to carriers and optimize marketplace bidding to maximize ROAS.

You will source data, monitor drift, and collaborate with an ML engineer on production deployment, shaping data for future iterations. We are remote-first with East Coast hours, empowering you to influence real-world outcomes across our performance platforms

Qualificações

• 5+ years of hands-on applied data science with measurable business impact.
• 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, neural network fundamentals included.
• You see how today's bids shape tomorrow's training data, and you've handled late labels, sparse features or drift.
• You own models end to end: you find your own data, build through deployment and monitoring, and bring a point of view.
• Expert Python and SQL

Responsabilidades

• Build and validate models to drive carrier matching and ROAS for the insurance marketplace.
• Source and prepare data, deploy models, and monitor drift and performance.
• Collaborate with an ML engineer on production integration.
• Frame problems with the business and deliver measurable impact.

Conhecimentos

Python,

SQL

Applied data science

Modeling for paid media

End-to-end ML

Production deployment

Drift handling

Ferramentas

AWS

SageMaker

Descrição da vaga

Launch Potato seeks an experienced data scientist to own end-to-end ML models for our auto insurance marketplace. You will build, validate, and deploy models that match shoppers to carriers and optimize marketplace bidding to maximize ROAS.

You will source data, monitor drift, and collaborate with an ML engineer on production deployment, shaping data for future iterations. We are remote-first with East Coast hours, empowering you to influence real-world outcomes across our performance platforms