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Senior Data Engineer / Data Scientist (M/W/D)

Senior Data Engineer / Data Scientist (M/W/D)

Bored by so-called strategic and growth oriented statistical analysis ending up nowhere? Tired of countless projects which start with a brilliant idea, a good data analysis and then get lost somewhere in on the way into production? You started your career with different goals, right?

We are searching for…

We are looking for you to help us as a data scientist / data engineer to realize our projects and products. You are passionate about innovation, about data-driven and machine learning enabled products. You do not want to get stuck with data analysis only but want to bring your ideas to life, apply your models to real data and test your hypothesis with real life users. It’s not about your Kaggle ranking but about delivering value through cool and intelligent products.

Well, your search is over. With us you can be yourself and follow your vision. We are building data-driven products (as for example a car recommender chatbot) and machine-learning enabled products (e.g. an automated language teacher). In order to do so we make use of exploratory data analysis, data engineering and machine learning. Of course, we do data analysis projects for our customers with the goal to implement our insights. And we help our customers to build up innovative and modern data platforms and products.


What you will do...

  • Take over end-to-end ownership for products, from data processing, to training, evaluating, to deploying and monitoring
  • Understand business objectives and translate them into digital products that leverage machine learning
  • Monitor data quality and work on feature engineering
  • Automate training and inference pipelines
  • Define model validation and monitoring strategies
  • Analyze the shortcomings of existing solutions and iterate on improvements
  • Introduce best practices that benefit the team and the product quality
  • Leverage synergy effects across teams
  • Shape the technology roadmap for data science & data engineering
  • Conduct knowledge sharing sessions
  • Enable product teams to ship data science powered products
  • Contribute to align future design and architectural strategies with the whole team

You are passionate about...

  • Exploratory data analysis: Jupyter notebooks, pandas, seaborn/matplotlib or rather workflow tools are your means to dive into the data, preprocess and analyze it. You love to visualize and clearly communicate your insights
  • Machine Learning / Deep Learning: established ML algorithms or latest deep learning research approaches - as long as they help you bring your ideas to life you confidently select, test, adapt and optimize them.
  • NLP / image recognition: unstructured data such as natural language (audio and text) fascinates you. And even more the countless possibilities currently opening up for intelligent products powered by speech, image and video data.
  • Data Engineering: you love clean, robust and automated data pipelines, infrastructure as code. The end-to-end perspective of a product where you control the process from data collection to using it in your model and then deploying it to production gets you excited.
  • You love the thrill of a new project, with new challenges where you have to be creative in finding possible solutions. After all you are not a machine who can endlessly repeat tasks without getting bored.
  • You enjoy the balance between working focused on a task and discussing concepts and ideas with the team.
  • You love to work together with customers and users in order to get new insights, a deeper understanding and valuable feedback for your approaches
  • You want to have an impact and build data products that make people's life easier and automates repetitive tasks
  • Sharing knowledge and onboard new team members

What we expect from you...

Requirements

  • Degree in computer science, data science, data engineering or similar
  • min. 4 years of relevant working experience (as full-time equivalent)
  • Knowing the whole process chain of data science and data engineering (including data thinking, data science, infrastructure as code, deployment to production, operation & maintaining)
  • Expert knowledge in at least one:

    • Data Engineering
    • Data Science
    • Machine Learning / Deep Learning Engineering
  • Experience with python and related data science libraries like Pandas, NumPy, Scikit-learn, Tensorflow, PyTorch, Keras etc.
  • Knows how to Terraform
  • Experience working with cloud-platform environments, such as AWS, Azure, or GCP

Soft Skills

  • You can work on your own and organize yourself.
  • At the same time you are a team player able to contribute to a goal you cannot reach alone
  • You are passionate about you work and want to deliver good quality and reliable products efficiently
  • You are driven by the desire to constantly improve yourself and learn new things
  • Curiosity to understand stakeholder needs und the business model
  • You push topics and lead the team through diverse projects
  • Ability to rethink fast and manage multiple projects at the same time
  • Fluency in English (German would be an advantage)

What we offer

  • Transparent salary structures
  • 4+1 working days (4 days of project work, 1 day for team exchange and work on favorite projects)
  • Free choice of hardware and software: laptop or workstation setup, smartphone, IDE
  • Flexible working hours
  • Home office if needed :)
  • Flat hierarchies
  • Individual personal growth plans, transparent levels for promotion
  • Events & conferences
  • One week surf-office
  • Free coffee, drinks, beer and fruit
  • Bike leasing

Das bieten wir dir:

Transparentes Gehaltsmodell

Individuelle Weiterbildung

4 + 1
Arbeitstage

Flexible Arbeitszeiten

+
Events
Konferenzen
Surf-Office
Produktfreitage

Equipment nach Maß & Wunsch

Lets go crazy

Manuel Lippmann


So geht es für dich weiter:

Erstes Kennenlernen.

1

Erstes Kennenlernen.

Im Rahmen eines ersten Gesprächs per Telefon oder direkt bei uns im Büro lernst du uns, unsere Arbeitsweise und was uns wichtig ist, etwas besser kennen. Auf der anderen Seite möchten wir etwas mehr über dich erfahren: was kannst du, was treibt dich an, was willst du erreichen? Danach entscheiden wir die nächsten Schritte.

Fachliches Gespräch.

2

Fachliches Gespräch.

In dem Gespräch lernst du deinen neuen Fachbereich kennen. Wir diskutieren gemeinsam mit dir die aktuellen Entwicklungen und deine bisherigen Erfahrungen. Meist ist auch eine kleine Testaufgabe oder sogar eine "Hausaufgabe" Bestandteil, um dein fachliches Wissen besser einschätzen zu können.

Cultural Fit.

3

Cultural Fit.

Jeder neue Mitarbeiter bereichert und ergänzt unser Team. Daher ist es wichtig, dass es auch menschlich zusammenpasst. In einem lockeren Gespräch mit Kollegen aus anderen Fachbereichen geht es darum, unsere Arbeitsweise und Werte zu vermitteln und deine Motivation und persönliche Vision zu verstehen. So stellen wir sicher, dass wir das was du erwartest, auch wirklich bieten können.


Senior Data Engineer / Data Scientist (M/W/D)

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