Вакансия Data Scientist

2 вакансии
Специализация: Data Science
Уровень: middle
Опыт: 2 года
Уровень английского: Не важно
Город: Минск
Размер команды: 13+
Размер компании: 50

InData Labs is a data science firm and AI-powered solutions provider with its own R&D center. Our main focus lies on machine learning and deep learning solutions, as well as building high-load data processing systems.

Currently, we are looking for a Data Scientist / Machine Learning Engineer who will be a part of the general-purpose data science team and work with tasks covering a wide variety of business needs without focus on computer vision. 

On this position, you will work with multiple data sources (usually numerical, textual and time-related data, less frequently visual data), huge and small datasets to develop, validate and deploy machine learning models, tune their performance & integrate them into data processing pipelines.


  • Deal with both structured and unstructured data, collaborate with data engineers on defining data storage formats, state data collection requirements;

  • Not only solve technical tasks but understand business needs and offer appropriate solutions, data collection and labelling requirements and recommendations, while describing a chosen approach to non-technical people;

  • Set up reproducible experiments: selection, training, validation and optimization of machine learning models, evaluation of their quality in business-related terms;

  • Integrate data preprocessing and model inference into general data processing pipelines;

  • Research new tools, papers, etc. in machine learning area.


  • Strong knowledge and deep understanding of

    • Сlassical machine learning (linear models, decision trees, ensembles for classification and regression tasks, clustering and dimensionality reduction)

    • Main concepts and stages of modelling process (validation scheme, regularization, overfitting and generalization, data leaks, feature selection, etc.)

  • Hands-on experience with Python scientific and ML-related libraries

  • Hands-on experience with gradient boosting libraries (xgboost, lightgbm or catboost)

  • Experience with relational databases and SQL

  • Ability to implement space and time-efficient algorithms and understand which one is preferable and when

  • Good Python programming skills

  • Data visualization and presentation skills;

  • Good spoken and written English (at least B1);

  • Ability and desire to convert raw business requests into strictly formulated machine learning tasks

  • Ability to formulate data gathering (or data labelling) requirements

  • Minimum 1-year experience in machine learning

Would be a plus:

  • Hands-on experience with developing parallel code in Python

  • Familiarity with non-relational databases (Cassandra, Elasticsearch, MongoDB, etc)

  • Experience in software engineering, deployment and integration with data delivery systems and other components, building microservices, providing APIs for models access

  • Experience in developing recommender systems, time series analysis

  • Experience in Natural Language Processing

  • Experience in Deep Learning with applications to any data domain

  • Experience in data labelling process setup using third-party or self-made labelling tools

  • Participation in ML competitions (Kaggle, etc)

  • Masters, PhD, or equivalent experience in Mathematics or Computer Science.

You will work with smart people who love to solve hard problems, and who not only expect but also foster high performance!

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