Senior AdTech Data Scientist: Autonomous Media Bidding

Launch Potato

Jersey City (NJ)

Teletrabalho

USD 175 000 - 200 000

Tempo integral

Há 3 dias
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Resumo da oferta

Launch Potato is seeking an experienced Data Scientist to build models that optimize insurance marketplace interactions and carrier assignments. You will own data exploration, feature engineering, and model deployment in production, with a focus on improving ROAS and conversion.

This remote-first role requires 5+ years hands-on data science, expert Python and SQL, and experience with production ML pipelines.

Qualificações

  • 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, 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 models that optimize insurance carrier matching on click wall.
  • Own buying models behind media spend and ROAS.
  • Develop production data pipelines and validate models.
  • Collaborate with ML engineers on deployment and monitoring.
  • Adapt models across verticals over time.

Conhecimentos

Python
SQL
Data science
End-to-end modeling
Experiment design

Ferramentas

SageMaker
Athena
S3
ECS

Descrição da oferta de emprego

Launch Potato is seeking an experienced Data Scientist to build models that optimize insurance marketplace interactions and carrier assignments. You will own data exploration, feature engineering, and model deployment in production, with a focus on improving ROAS and conversion.

This remote-first role requires 5+ years hands-on data science, expert Python and SQL, and experience with production ML pipelines.

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