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Data Scientist – Pricing (f/m/d)


Role Description

SIGNA Sports United is growing its data science team for pricing and looking for Data Scientists to develop tools to continuously improve our automated/AI-driven pricing decisions across our group companies.

As Data Scientist in the pricing team, you will partner with pricing managers and use our large and rich datasets to develop tools for demand forecasting and better understand the price elasticities of our large assortment of products. The position requires a sound knowledge of statistics to help to formulate a well-defined business question, and the ability to tell cause and effect relationships from correlations. Also importantly, the Data Scientist requires excellent programming skills as well as the ability to convey business insights to non-technical members of the team. This is a challenging position, that has a large impact on the everyday operations of our group of companies, and that will ultimately help us in our mission to become a data-driven organization.

- Collaborate with stakeholders to refine a vague problem statement and formulate the right question.
- Design, implement, evaluate ML algorithms, and carry out the statistical analysis to provide insights for decision making.
- Summarize and communicate to technical and non-technical audiences the results from the data analysis and the underlying assumptions.
- Write reproducible data analysis using terabytes of data from business units across Europe.
- Build data pipelines


Basic Qualifications
- M.Sc in a quantitative field (applied mathematics, statistics, econometrics, computer science, machine learning, data science or equivalent) or related experience
- Knowledge of at least one modern open-source programming/scripting language for data science such as Python or R.
- Ability to determine cause and effect relationships.
- Ability to communicate results clearly to both colleagues and peers on the team as well as less technically versed audiences
- Independent, driven and looking to make an impact using data-driven solutions
Preferred Qualifications
- PhD in a quantitative field (applied mathematics, statistics, econometrics, computer science, machine learning or equivalent)
- 3+ years of professional experience working in data science in e-retail
- Skilled with specific libraries for data analysis and visualizations including jupyter, pandas, numpy, scikit-learn, dplyr, xgboost, parallel, etc.