Data Scientist (f/m/d) wanted for Berlin! Ref.Nr. ...

Company:
Location: Home Office

*** Mention DataYoshi when applying ***

For an international customer we are currently looking for Data Scientist (f/m/d).

Aufgaben

  • Implement an unsupervised deep learning based anomaly detection approach for imbalanced data
  • Document the training techniques employed for the solution
  • Implement the code in Python 3.7+ and either Pytorch or Keras (Tensorflow 2.0+) as the Deep Learning framework
  • Ensure the code is available and reproducible on a GPU-enabled Linux machine
  • Ensure all data, code used, workflow (including pre-processing and featureextraction), training and hyperparameters are tracked for every reported result
  • Document the limitations of the approaches and recommend constraints to improve the performance of the Anomaly Detection algorithms
  • Cooperate with the team through weekly 30-60 minute calls to discuss hypotheses being tested, findings and blockers or questions for domain experts
Qualifikation

  • Proven experience in Time Series analysis with Deep Learning approaches applied to industrial datasets
  • Experience in other Machine Learning methods for time series analysis and applied statistics
  • Comfortable with Pandas, Scikit-Learn, Numpy and either Pytorch, Tensorflow or another common DL framework
  • Some experience with semi-supervised and self-supervised methods on structured data
  • Some experience in NLP with non-academic datasets
  • Some experience with at least one Python API framework
  • Excellent communicator English
  • Ideally: Some experience with Git, Docker and experience scaling ETL pipelines
Order type: Contract

location: Berlin/remote

Start: asap

Duration: 6 month ( with option of extension)

If you are interested, please tell us about your hourly rate and your availability. We are looking forward to your application in an MS-Word-readable format quoting the reference-number 2755.

Any Questions? Call +49 152 289 826 27.

*** Mention DataYoshi when applying ***

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