Data Science Engineer

Published on Aug 03, 2021

A Product company with office in Kyiv, Ukraine.

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1-3 years
Job Type:
Data Engineering
Deep Learning
Data Science & AI

What You Will Do Responsibilities
  • Bring new ideas in software development
  • Leverage industry knowledge and stay close to technology developments
  • Collaborate with cross-functional teams

What You Should Bring
  • Work experience: 3+ years
  • Strong expertise in:
  • Machine Learning and Data Science
  • Statistics (probability distribution, hypothesis testing)
  • Classical ML algorithms (Linear Regression, Decision Trees, SVM, Clustering, etc.)
  • MLOps (BentoML, Docker, Kubernetes, KubeFlow, KNative)
  • Python (PyTorch or Tensor)
  • General programming skills (OOP, OO design, MVC, Design patterns)
  • Solid understanding of ML/DS processes (from data preparation to model deployment)
  • Proven portfolio of successful projects
  • Participation in team projects
  • Good verbal and written communication English skills (Upper Intermediate level)
  • Experience in data extraction, cleansing, and preparation for ML training and test data sets
  • Experience in analysis of structured and unstructured / semi-structured data (e.g. raw text, json, xml)
  • Statistical Analysis & Modelling experience
  • Good knowledge of Predictive Modelling, Regression and Classification techniques
  • Good knowledge of Deep learning tools and techniques
  • Understanding and knowledge of Natural Language Processing (NLP) applications
  • Any BigData platform knowledge and/or experience (Apache Spark, Hadoop, Hive etc)
  • Hackathons/Kaggle experience
  • Data Visualisation (e.g. using Python, Tableau, R Shiny)
  • Hands on experience developing with relevant Python toolkits
  • Experience with:
  • C# and .Net
  • Go, Scala
  • DataRobot, Chatterbox Labs, Google ML, Ludwig
  • Working with sensitive data
  • Desirable Data Engineering skills
  • General knowledge of enterprise data architecture and data modelling
  • Relational database modelling including transactional systems and data warehousing
  • NoSQL databases e.g. MongoDB, Cassandra, Elasticsearch, Graph databases
  • Experience working with Unix command line and shell scripting
  • Cloud Architecture or Engineering experience with emphasis on data and analytics services
  • Relevant certifications in Microsoft Azure or AWS
  • Knowledge of deployment specifics of ML models in CI/CD
  • Hands-on experience with microservice architectures and containerisation (e.g. Docker and Kubernetes)
  • Experience developing and working with REST APIs

What You Will Get Benefits
  • Medical Insurance;
  • 20 working-days paid vacation and other social benefits;
  • Mid-year and annual performance review with a constructive feedback and development plan;
  • Continuing education/training;
  • Free access to global online educational platforms;

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