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Staff Data Scientist

Incrmntal · Ramat Gan, Tel-Aviv District, Israel

Software Development · 11-50 employees

Jul 16
Remote Mid (2-5 yrs) Full-time Israel
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About the role

The Staff Data Scientist will lead the development of algorithms for automated decision-making, including causality and multi-touch attribution. They will also analyze core marketing metrics to identify causal relationships and translate complex data into actionable business recommendations.

What they look for

Python Statistical modeling Causal inference Bayesian methods Spark Airflow Kubernetes Time series analysis Machine learning Data science Marketing analytics Distributed computing Prediction models R Scala

Requirements

Candidates must have at least 3 years of experience in a commercial data science environment with strong statistical and engineering skills. Proficiency in Python and experience with big data tools like Spark and Kubernetes are required.

Full description

Role Description:

As a Staff Data Scientist your role will be to:

  • Use analytical, statistical and technical skills to understand large, complex datasets with the aim to eliminate waste and measure incrementality for advertisers.
  • Lead, Develop & improve algorithms for automated decision making around lifetime value, causality, multi-touch attribution, and media mix optimization
  • Determine, analyze, maintain, and report on core marketing metrics to identify causal relationships between marketing actions and outcomes.
  • Translate data into actions and recommendations – appropriately interpreting and building on findings, and fully exploiting insights

You will also participate in important decisions around the product, our strategy as well as have the opportunity to choose the areas you work on based on what you want or like to do the most. We believe in helping each other get most of ourselves rather than do what we’re not interested in doing.

Key Requirements:

  • Min. 3 years of work experience in a commercial data science environment that requires the combined application of statistical & engineering skills
  • Strong statistical and research skills with a track record of using a variety of math and statistical methods (especially Causal Inference, Prediction models, Bayesian Method)
  • Excellent development skills (Python required, R or Scala a plus)
  • Experience in working on big data with distributed computing (Spark, Airflow, Kubernetes)
  • Familiarity with digital marketing, advertising or analytics is a plus
  • Extensive experience in the Time Series domain, working with small and large time series frames
  • Theoretical background knowledge like from a relevant BSc, MSc or PHD is a big advantage (e.g. in Mathematics, Computer Science, Statistics, Physics)