Data Scientist

vor 2 Wochen

Berlin, Deutschland Arbolitics Vollzeit

Arbolitics GmbH, a Berlin-based agricultural data analysis company, is looking for a Data Scientist with a strong focus on Machine Learning. We have a dynamic environment and a small team so we require a high degree of proactiveness and creativity to solve problems and innovate effectively on those. It is our second company in the space, the first one was recently acquired by an industry holding.  


Data Scientist (ML) (f/m/d)


Required Qualifications:

  • 3 Years of Machine Learning Experience: Must have practical experience in applying machine learning techniques.
  • Python Proficiency: Ability to produce clean, efficient, and well-documented Python code.
  • Advanced Knowledge of Machine Learning Models: Deep understanding of modern machine learning models and capacity to translate academic research papers into code.
  • Machine Learning Frameworks: Demonstrated experience with Pytorch or Tensorflow.
  • Data Preparation Skills: Ability to transform raw data into datasets optimized for training, ensuring high-quality inputs for model development.
  • SQL Skills: Strong capabilities in data manipulation and analysis using SQL (PostgreSQL).
  • English Communication: Excellent written and verbal communication skills in English.
  • Git Experience: Familiarity with Git and collaborative coding practices.


Desirable Qualifications:

  • End-to-End Project Experience: Completion of at least two end-to-end projects in areas such as computer vision, recommendation systems, or regression analysis.
  • Technical Documentation Skills: Experience in preparing clear and concise technical documentation.
  • Knowledge of Docker and Model Serving: Familiarity with Docker and practical experience in model serving.


What we offer:

  • An opportunity to be part of a passionate, international team making a real impact on agriculture and climate change
  • Competitive salary, potential equity participation
  • Professional development and growth opportunities
  • Flexible work schedule and hybrid work opportunities

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