(Senior) Data Scientist

What we are planning together:

As the Analytics division of REWE Group, we are part of the Executive Board department for Digital & Technology, bringing together all strategic, analytical, and business support functions within Handel Deutschland under one roof. The division aims to establish Advanced Analytics and Artificial Intelligence as a capability and value driver in all essential business decisions at REWE. Agile working methods and a modern technological environment provide the perfect working environment to drive the development of analytical products and use cases. Be there when AA & AI are elevated to a new level in German food retail!

What you will achieve with us:

Do you want to make a real difference with your ideas and developments? Do you also enjoy logic and tinkering with complex problems? Then you'll find what you're looking for with us! As a (Senior) Data Scientist at REWE Group, you will significantly shape the shopping experience of millions of REWE and PENNY customers in the German food retail sector and repeatedly encounter tricky analysis questions.

Deliver value:

As a (Senior) Data Scientist, you will independently drive exciting and challenging advanced analytics projects in the food retail sector to sustainably optimize decision-making processes and take a leading role in the data science strategy and unlocking business potential.

Manage the entire product lifecycle:

You will be responsible for the end-to-end development and operationalization of complex models and machine learning pipelines for use cases in forecasting, classification, recommendation, and scoring, and for their continuous quality control.

Keep the big picture in mind:

You will manage structured and unstructured data in various database systems (e.g., GCP/BigQuery, Snowflake) and analysis frameworks (e.g., Hadoop/Spark).

Bring everyone together:

Joint development of analytical products in agile and interdisciplinary teams, as well as proactive and steering collaboration with the business department and internal stakeholders to transform data into business-relevant insights.

Lead by example:

Provide technical guidance and coaching to junior colleagues. Develop standards and ensure that best practices in methodology and code are applied.

What convinces us:

First and foremost, your personality: Your very good analytical and conceptual thinking skills combined with strong communication skills – especially towards non-technical colleagues and listeners – and your passion for data analysis and your very good German language skills. Your ability to quickly understand new, challenging business questions and to answer them flexibly with precisely tailored analytical models. That you have a high service and team orientation, enjoy working in an agile and very dynamic environment, and are always up to date with technologies and developments.

A completed Master's degree with a Data Science/Analytics focus (e.g., Business Informatics, Statistics, Econometrics, Computer Science, Mathematics, Physics, or similar). A business administration focus and/or a doctorate are also welcome. Furthermore, your proven practical experience in data analysis and in Data Science/Big Data projects – preferably in cloud environments – and that you master the development and deployment of analytical software solutions throughout the entire product lifecycle, especially the operationalization and monitoring of ML models. Your very good programming skills with solid practical experience in Python and SQL. You are very familiar with common data science libraries & tools such as scikit-learn, pandas, Matplotlib, and Jupyter and have experience with Big Data frameworks like Apache Spark. Knowledge of professional software development methods, including version control (Git), CI/CD, and containerization (Kubernetes), is also welcome.

What we offer:

REWE Group, as one of the largest retail and tourism groups in Europe, offers unique opportunities for everyone who wants to make a difference. Discover a down-to-earth employer that trusts you, provides scope for creativity, and promotes innovation and fresh ideas through flexible structures. Those who work with us and achieve a lot can also expect a lot:

• Attractive remuneration: With special benefits such as vacation and Christmas bonuses, capital-forming benefits, company pension plans, subsidies for the canteen and a subsidized Deutschlandticket, as well as benefits for bicycle leasing.
• Employee discounts: At REWE, PENNY, toom Baumarkt, and DER Touristik.
• Work-Life-Balance: With flexible working hours without core hours, home office, leave of absence models, company daycare centers, modern parent-child offices, and support in finding childcare and caregiving.
• Personal development: With extensive seminar offerings, subject-specific academies, tech talks, e-learning, and participation in conferences and hackathons.
• Health management: With preventive medical examinations, sports, health, and cooking courses.
• Scope for design: Co-determination in the selection of algorithms, analysis techniques, and technologies, and independent work on exciting questions from various business areas (Supply Chain, Logistics, Marketing, Customer Service).
• Agile environment: Collaboration with agile development teams in the Big Data context.
• Connected: Company-wide networks of REWE Group, such as our LGBTIQ network "DITO – different together" and the women's network "f.ernetzt" for exchange on career and personal development.

In our mini-podcast, you can learn more about the daily work of a Data Scientist from Hannes. You can find all further information about the Analytics division here. You can get more information at jobs.rewe-group.com. We look forward to receiving your online application, including your availability and salary expectations. Unfortunately, we cannot return paper applications.

Do you have questions about this position (Job ID: 829295)? Then contact our application hotline at 0221 149-7110. We expressly emphasize that everyone is equally welcome here – regardless of gender/gender identity, ethnic origin and nationality, social background, religion/belief, physical and mental abilities, age, or sexual orientation or other individual characteristics.