Data Scientist

Experience: 1-3 years
Minsk, full-time

Domains:

  • fintech;
  • publishing;
  • healthcare;
  • manufacturing;
  • corporate portals and internal labs.

What we expect:

  • сommon knowledges: Machine Learning, Deep Learning, NLP, recommender systems, data manipulations with big data (preferably in GCP), work with DWH;
  • OS: knowledges of Linux user, service manipulations, BASH scripting;
  • knowledges and skills in SQL and NoSQL (preferably PostgreSQL, BigQuery, Redis, MongoDB);
  • development: Python, scikit-learn Tensorflow, Keras, Pandas, NumPy, XGBoost, CatBoost, deploy models to prod with RESTful API for Flask;
  • english level: Intermediate or higher.

What you will do:

  • building models based on classical algorithms such as KNN, regression, decision trees etc.;
  • building and finetuning of neural networks models;
  • building and finetuning of neural networks models;
  • deployment models to production;
  • A/B testing, data analysis, interpretation and visualization;
  • research & reporting for business needs;
  • data quality control;
  • active participation in the development of solutions: creating and implementation of businesslogic, participation in architecture design of ETL-pipelines and DWH;
  • communication with the customer, understanding of the customer’s problems from a business perspective, decomposition of the problem/requirements for subtasks;
  • knowledge sharing and internal trainings.

Nice to have:

  • familiar with Docker, Jenkins (simple jobs and pipelines);
  • familiar with visualization & dashboarding using Google Data Studio;
  • familiar with Terraform;
  • have Golang knowledge/experience;
  • have experience in Kaggle competitions;
  • have certificates from Yandex or Google courses in Coursera (DS or Big Data Specializations);
  • familiar with ETL Tools: Spark, Apache Beam;
  • familiar with Kubeflow or other reproducible model deployment tools;
  • knowledges in Google Cloud Platform: common architecture understanding, cloud load balancing, managedgroups, GCS, GCE, PubSub, Cloud Dataflow, Dataproc, BigQuery, Cloud Source repositories (Git), Cloud Build & triggers, AI Platform for model deploy;
  • postgraduate student (have researcher’s diploma).

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