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Machine Learning Engineer / Data Scientist

Synerise is looking for Machine Learning Engineer who are in common with new technologies and have need to develop himself (or herself) and work on comprehensive product with us! If you have great analitical skills and knowledge about machine learning and want to work on implementation these algoritms into our marketing and omnichannel platform - read this offer to the end - this may be something for you!  

Are you ready to:

  • meet big challenges and work with big amounts of data?
  • develop the most comprehensive marketing tool and have real influence on it?
  • work on implementation machine learing solutions and really predict the future from collected data?
  • think about your own development and want to work on really big projects with international clients?
If yes, prepare yourself for a great challenge and take a chance to develop your skills working on our flagship product.

It would be great if you have:

  • experience in the field of Machine Learning
  • passion for programming, building tools and automating everything
  • good knowledge of data stacks; Pandas, NumPy/SciPy, Spark, Matplotlib, Jupyter, scikit-learn
  • acquainted with techologies: Hadoop, MapReduce, TensorFlow, Elasticsearch; HBase, Spark ML, Spark Streaming
  • good knowledge of Pyhton, Scala and R is required
  • strong analitical mind
  • paying attention to details and quality
  • good level of English (both verbal and written)
  • high motivation for self-development and a desire to acquire new skills

We will appreciate your work with:

  • attractive salary based on your professional experience and skills
  • full support of the proposed initiatives
  • ideal tools - you will get the hardware and software choosen by you
  • possibility of personal development and acuring new skills
  • great working environment with still developing team in friendly atmosphere
  • flexible working hours


  • designing and developing algorithms for advanced analytics & data science using technology like Spark Streaming, HBase, Hadoop
  • developing architecture and design patterns to process and store high volume data sets
  • developing software with a core focus around optimisation and performance
  • playing a key role in analytical projects from beginning to end
  • using statistical methodologies and analyze data

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