(Senior) Data Scientist / Analyst - Statistics, Causal Modeling & Analysis (f/m/d)

Who we are

We operate Kaufland.de: Several thousand sellers and millions of products make us one of the fastest growing online marketplaces. Our work is characterised by a dynamic corporate culture, with a start-up mentality and the power of a big corporate group. We combine knowledge and many years of experience in e-commerce with flat hierarchies and a highly motivated team. Whether it's from an intern: We take every idea seriously, because we want to work together in shaping the future of e-commerce!

We love flexibility! We offer you the best environment to work in a flexible and focused way: You decide whether you want to work in our office in Cologne // Darmstadt // Düsseldorf while at the same time having the opportunity to work remotely (Germany). We want to offer you the most attractive workplace in e-commerce and a maximum of flexibility for your personal work-life balance.

Day-by-day, our development team of over 250 experts pursues the goal of creating the best-possible customer shopping experience for the Kaufland marketplace. We are here to inspire millions of customers, to help them find, purchase and get the things they love. To enrich the lives of our customers, we collaborate in cross-functional teams, in which product owners, product designers, frontend and backend engineers, data scientists and lean managers join forces. Details regarding the challenges of the respective product areas can be found here: https://kaufland-ecommerce.com/team/tech/.

Your task – this awaits you in detail

  • As a (Senior) Data Scientist (f/m/d) in this role, you will build and enable our ability to make data-driven decisions, often based on A/B tests.
  • Here are some examples of questions that you will deal with: Do customers who experience a delay in their delivery tend to come back less often? If so, is the difference significant and is the delay even the root cause or does the causality lie in the originating country of the sellers they bought goods from or the types of goods themselves? Do products with free shipping or faster shipping have higher conversion rates? Does this apply to all product segments? And if so, is this a causal effect or is it just a correlation that is grounded in a selection bias?
  • You will have access to vast amounts of data such as time series sales data, natural language unstructured product information, and customer behavioral data to dig in and help uncover relationships to improve our customer experience and business.
  • You will be responsible for finding the best approaches and solutions to solve business challenges, design data sets, and of course, build analytical and machine learning models to answer research questions.
  • You will work closely in a smart and fun team with other data scientists, machine learning engineers, business intelligence analysts, web analytics specialists, and of course closely with product managers and other stakeholders.

Your profile – this is what we expect from you

  • You have a university degree in mathematics, computer science, information systems, or the like.

  • You have proven experience with statistical modeling and causal analysis, ideally in the Python ecosystem. Experiences in related fields such as machine learning, predictive analytics, natural language processing, or deep learning are a plus.

  • Experience with behavioral web analytics data such as from Google Analytics is a plus.

  • You have or would like to work in a business-aware environment, thinking “end-to-end” over just solving a theoretical problem.

  • You are used to finding your way around data sources, including a good knowledge of SQL or SQL-like dialects – ideally with large data sets.

  • You are proficient in the programming language that is the weapon of your choice, ideally Python, and have a good understanding of the respective package ecosystem.

  • You have excellent communication skills, are willing to embrace our company culture and values, and enjoy working in an international, English-speaking team.

What we offer

  • Create your own work-life! We offer you the best possible flexibility in terms of working hours and location 
  • A highly-motivated and qualified team from different fields and numerous nations
  • The future is digital - Develop the e-commerce of the future with us and work on a product with millions of users with a broadly-based technology stack
  • Power meets dynamic - flat hierarchies and start-up mentality meet and the power of a big corporate group and offers you an agile and secure working environment at the same time
  • Free choice of hardware – we provide you with the development environment of your choice
  • Personal & team growth: We love to have flexibility in terms of working location, but we also believe that personal interactions are important. That’s why we organize company events, and cover the costs to bring you there and to other (approved) get togethers with your peers. The same applies to conferences and other learning opportunities. We want everybody to grow personally and professionally, as a team and as a company.
  • Top conditions at the Urban Sports Club for fitness, team sports, yoga and more
Check out our Principles & our blog for even more insights into our company culture!

Refer an Engineer Program

You want to work for us, but not without your dearest colleague? Join us as a team and earn money by referring your buddy for one of our open Tech positions! Depending on the level we offer a bonus up to 1.300,- € per referral, which will be paid after successful recruitment (the first part with your first salary, the second part after your buddy passes the trial period).
Why are you the perfect fit for this position? Don't bother with cover letters - we're interested in facts and figures! 
Bewerben
Your contact person: Lea Sycha
Kaufland e-ecommerce
Kaufland e-commerce Services GmbH

Postal address:
Habsburgerring 2
50674 Köln

We're looking forward to your application! 

Offene Stellen