Job description

Are you passionate about energy efficiency and sustainability? Are you looking to work on enabling Industrial Internet of Things (IIoT) applications for Maritime industry? Can you add more senses to everyday objects and spaces? Do you possibly have a small home automation project of your own? Big data and artificial intelligence are not just buzzwords but familiar concepts for you?

If that resonates with you, you might be the Data Scientist ALFRED Maritime GmbH is looking for! Jump in and join our enthusiastic core team to craft completely new things for the maritime industry. The core team’s ultimate mission is to make greener future for the shipping industry using machine learning and the smart controls.

We also acknowledge that our task is not easy and therefore customer collaboration is of utmost importance and essence to succeed. In practice this means working with, listening, and learning from the numerous subject matter experts in the maritime sector.

Here Are Some Qualities We Are Looking For

  • Highly motivated, outgoing, and creative individual who really believes work can be fun.
  • Passionate to improve and adapt the today’s technologies for a better, greener, tomorrow.
  • Enjoy venturing with new technologies and not at all afraid of creating something completely new what hasn’t been done before.

Your Responsibilities Will Be

  • To understand the big picture and work with SMEs to arrive at business case.
  • To quickly visualize and test hypothesis based on data for a given problem.
  • To design, develop and optimize predictive data models to a given problem that can save costs, increase sustainability, create more revenue, or simply create completely new revenue streams.
  • To question the status-quo of an existing industry practices and lead it into new greener waters.
  • To analyze data and develop algorithms to process, assess and clean data.
  • To collaborate with diversely skilled core team and come up with ideas for installing new sensors and IIoT infrastructure components for identified problem.

Keys To Success In This Role

  • Master/PhD in STEM subjects or equivalent.
  • Excellent written and verbal communication skills in English. German and Finnish is a bonus but working language is English.
  • A good understanding of software best practices (versioning (GIT), profiling, clean code (PEP standards), debugging etc.) as well as ML techniques (data cleaning, preprocessing, feature engineering and hyper parameter tuning etc.).
  • A good handle on ML/DL methods for time-series prediction/forecasting.
  • 3-4 year field experience in data science or an equivalent outstanding academic record.
  • Strong programming background (Python preferred) and ability to write queries for SQL and NoSQL databases.
  • Good experience in building Data models for new business domain from production quality data with high throughput, veracity and verity with no or limited access to existing reference data models.
  • Good understanding of popular ML Frameworks (i.e. TensorFlow, Apache Spark etc ) and varied managed ML services offered by Azure/AWS/GCP etc. providers.
  • Ability to understand the big picture in the overall architecture on how the varied data set, data models fit it to solve a business problem.
  • Good interpersonal and teamwork skills with ability to work in international team.
  • Helps: Experience in working with Scrum.
  • Plus: Experience in cloud technologies (preferably Azure) is seen as a big bonus.
  • Big plus: Experience in working with operational data sets of IIoT or Smart building environment.

What We Offer

We offer you a flexible hybrid office environment, competitive salary, access to an online professional training platform amongst other perks like sponsored gym membership, Deutschland ticket and bicycle or an e-bike lease.

At ALFRED you sit at the front seat for watching and defining the shape of cruise vessels in the future.

Please send us your application in English, including your salary expectations and earliest possible starting date.

If you have any questions, please contact Kathrin Ballin-Fisch (

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