Staff Data Scientist
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The role in plain words
- Min. 3 years of work experience in a commercial data science environment applying statistical and engineering skills
- Strong statistical and research skills (Causal Inference, Prediction models, Bayesian Methods)
- Python
- Experience in working on big data with distributed computing (Spark, Airflow, Kubernetes)
- Extensive experience in the Time Series domain
- R or Scala
- Relevant degree (BSc, MSc, or PhD in Mathematics, Computer Science, Statistics, Physics or similar)
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Who this suits
Full job description
Original listing · kept for referenceRole 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)
Questions about this role
- This listing did not state a salary. We only show pay when the employer publishes it.
- Min. 3 years of work experience in a commercial data science environment applying statistical and engineering skills, Strong statistical and research skills (Causal Inference, Prediction models, Bayesian Methods), Python, Experience in working on big data with distributed computing (Spark, Airflow, Kubernetes), Extensive experience in the Time Series domain