At Transporeon we embrace transformation and change in total sync with one another. We rethink, reinvent and rework ideas from one moment to the next – as many times as is necessary to get the job done right. That’s how we respond to the new challenges that we face each and every day. And regardless of whether you are just starting your career or are already a pro – we believe you can be the transformation. Are you ready?

You can find more information about Transporeon as an employer here >>

Data Scientist (x/f/m)

Your transformation challenge?

  • we sieve through vast amounts of transport data from manufacturing companies as well as their logistics partners and even the trucks telematics systems, and make magic by assembling it all into our Transport Management Platform
  • you will get a unique possibility to use an immense amount of data and work on designing, developing, validating, and deploying data-driven products to improve logistics processes
  • there are challenging questions which you will answer through independent research, evaluation and usage of modern processes and methods from the area of predictive analytics, machine/deep learning and artificial intelligence
  • get to work truly end-to-end: we give you ownership to be involved in the whole process, you will work with data, clients, engineers and product managers to turn ideas to requirements,  to smart algorithms and make sure it works correctly even after deployment

Possible countries of employment:

Estonia, Germany, Poland, Italy, Austria, The Netherlands, Belgium, France, UK, Denmark, Sweden, Latvia, Finland, Slovakia, Spain, Portugal

You are ready, if you ...

  • own strong analytical skills, innovative thinking and are able to quickly use new technologies and their possibilities to answer complex questions
  • are able to transfer results of your thoughts and concepts into compelling visualizations and presentations understandable to our key stakeholders
  • bring at least 2 years of relevant industry experience
  • are proficient in tools from the wider PyData ecosystem, such as Pandas, NumPy, SciPy, scikit-learn, XGBoost or TensorFlow
  • have experience in machine learning using advanced algorithms and architectures to tackle regression, classification or time series forecasting problems; skills in MLOps on AWS or GCP are a great plus
  • are familiar with databases and SQL, especially Redshift, BigQuery or PostgreSQL, either to support your own exploratory data analysis or to generate insights for key stakeholders

Our tech-stack:

  • AWS, GCP
  • Redshift, BigQuery, PostgreSQL
  • Kubernetes
  • Python, Jupyter notebooks
  • Tableau, Looker