Back to all jobs

Data Scientist (m/f)

Permanent employee, Full-time · Berlin

About us
Minodes is a young high-growth technology business fundamentally transforming the way brick and mortar retailers engage with their customers. Headquartered in Berlin, we provide global retailers with innovative SaaS solutions on a mission to enhance the consumers’ shopping experience and give brick and mortar retailers an edge over their online competitors in an increasingly digitized world. Our dynamic and ambitious team combines expertise from top players in retail, VCs, internet and tech startups. You will enjoy having high impact in a company with tremendous growth potential, giving you unparalleled opportunities for growing personally and professionally.
About the job
Do you love big data and machine learning? Do you have a strong passion for empirical research and for answering hard questions with data? If yes, you will love working at Minodes!
At Minodes, we empower our clients in the retail market with analytical tools to understand how people move inside and nearby shops. We deploy machine learning and data processing at scale in our data analytics pipeline, and constantly evaluate new state-of-the art technologies to delight our customers with better results.
As a member of the Data Analytics team, you will be exposed to a modern technology stack and a slick agile team setup. You will be in the unique position to experiment with very large and proprietary datasets of wifi signals and mobile network data on a diverse set of challenging problems.

You will be responsible for

  • Designing and implementing efficient and robust scalable solutions for hard problems with state-of-the-art machine learning and data mining pipelines, taking care of any other data engineering and processing requirements
  • Collaborating and leading the conversation with business stakeholders within our organization
  • Taking ownership of your projects and finding new opportunities and problems where machine learning could be applied to improve the business
Who we are looking for
  • M.Sc. degree (Ph.D. is a plus) in Engineering, Mathematics, Physics, Statistics or Computer Science
  • Broad and deep understanding and practical knowledge of machine learning and data mining algorithms
  • Solid programming background (ideally both Python and Scala)
  • A proven track record of implementing data driven products
  • “How can I help” mentality, excellent communication and team collaboration skills
  • Sense of ownership: you take responsibility for your projects and pride in your work

Not a must, but we appreciate the following skills

  • A passion for using and developing open source software
  • Programming experience with data processing frameworks (Spark, Flink, etc.)
  • Experience with Python scientific libraries (pandas, scikit-learn, xgboost, keras, tensorflow, etc.)
  • Experience with big data technologies (Hadoop, Cassandra, NoSQL, etc.)
  • Experience implementing data infrastructure solutions in AWS
What we offer
  • A startup growing at a fast pace and boosted by the resources of our mother company Telefónica NEXT
  • A great, motivated and international team to work with
  • Lots of opportunities for learning and personal growth
  • A competitive salary
  • A modern office in Berlin near Checkpoint Charlie with many perks regarding work ergonomics
  • Free drinks, breakfast, snacks and a Playstation 4 
We're looking forward to receiving your application including a compelling motivation letter, a clearly arranged CV, your earliest possible starting date as well as your salary expectation.

About us

Thank you for considering a career at Minodes GmbH. Please fill out the following form. In case you are experiencing problems with the document upload, mail your documents to

Please upload any documents that you want to include with your application. CV and cover letter are required, and you should also attach copies of your references and certificates.
In order to upload multiple files, please select them in one go by using the CTRL key on Windows or the CMD key on Mac.