Data Scientist - Experimentation & Causal Inference (m/w/x)

About Schwarz Digits

Schwarz Digits creates the technological foundation for digital decision-making freedom in Europe. As the IT and digital division of the Schwarz Group, we develop and manage the IT infrastructures for the retail divisions Lidl and Kaufland, as well as Schwarz Produktion and PreZero. At the same time, we operate as an independent provider in the external market, supporting companies across Europe in their digital transformation. Our core services are bundled in the areas of Cloud, Cyber Security, Data & AI, Communication, and Workspace. Contribute to digital decision-making freedom in Europe.

With us, you work at the interface between agility and security: You benefit from fast decision-making processes, enjoy real scope for design in your projects, and build on the stable foundation of the Schwarz Group.

About the Team

In the Data Tech & Enablement area, we shape data-driven decisions along the entire customer journey of our internal customer Lidl Online. Our team is proud of its methodological depth and technical excellence – and this is where you come in: To take our experimentation culture to the next level and scale our systems for the future, we are looking for methodologically excellent and technically adept reinforcement who can seamlessly translate statistical theory into productive code.

Your Tasks

• End-to-End Experimentation: You are responsible for the experimental design and statistical evaluation of our A/B tests in the pricing & marketing environment. You will master challenges such as power analyses, randomization strategies, and the methodologically sound interpretation of complex test results.
• Scalable Implementation & Tooling: You are not only a consultant but also actively develop. You write production-ready code (Python/SQL), develop the statistical core functions of our internal A/B testing app, and integrate automated statistical workflows into our cloud data landscape (GCP/Databricks).
• Methodological Spearhead: You evaluate and implement advanced statistical methods (e.g., sequential analysis or Bayesian approaches) to continuously improve the efficiency and validity of our experiments.
• Statistical Consulting: You are the first point of contact for product managers, analysts, and data engineers on statistical questions. You help to avoid bias and ensure the validity of our results.
• Knowledge Transfer & Succession: You take on a key role in a long-term planned generational change. During a 3- to 6-month onboarding phase, you will work closely with our departing expert to acquire deep domain knowledge and lead the statistical excellence in the team into the future through modern tech approaches.

Your Profile

• Education: Completed studies (Master/Diploma) in Statistics, Mathematics, Computer Science, Econometrics, Data Science, or a related quantitative field with a strong focus on inferential statistics.
• Experience: You have sound professional experience (approx. 2-5 years) in statistical modeling, ideally with a clear reference to A/B testing or experimentation in the digital/e-commerce environment.
• Tech Stack & Engineering: You are extremely proficient in Python and SQL. The application of software engineering best practices (Clean Code, OOP, version control with Git) is a matter of course for you. Ideally, you have experience with PySpark and cloud infrastructures (GCP/Azure) or Databricks.
• Methodology: Concepts such as p-values, confidence intervals, Type I/II errors, and multivariate tests are your daily tools. Experience with Sequential Testing or Causal Inference is a big plus.
• Communication: You have the ability to explain complex statistical concepts understandably to non-statisticians and enjoy acting as a bridge builder between Data Engineering and Business.
• Languages: As we are an international team, you communicate confidently in English. German language skills are a clear plus for smooth knowledge transfer during the onboarding phase.