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Must-have:

Languages: Python, JS
Libraries/Frameworks: Keras, Tensorflow, PyTorch, sklearn, numpy, pandas, spaCy, PySpark, Vue.js и др
Distributed Computing: Spark
Cloud Platform: AWS (AWS ML)
CI/CD: Docker, Kubernetes
DB: PostgreSQL, MongoDB и др.
высшее или неоконченное высшее образование в IT или физико-математическом направлении;
знание основ статистики и теории вероятностей;
знание основных методов кластеризации и классификации;
знание и базовый опыт программирования на Python;
знание библиотек для работы с данными numpy, pandas;
знакомство с фреймвёрками TensorFlow или PyTorch;
опыт работы с базами данных и знание языка SQL;
английский на уровне чтения и понимания технической документации.


Must-have:

5+ years of experience in Data Science
Experience with R&D of model’s strategies
4+ years of experience with R/Python
Sales data or Inventory analysis experience
Experience with Databases (MS SQL Server) 
Deep knowledge of GLM/Regression, Decision Trees, Time Series, PCA
Experience in Feature selection, Transfer Learning, classical Machine Learning, AI techniques
Master’s degree in Computer Science, Statistics, Applied Math or other related areas 
English level: Upper-Intermediate+


Must-have:

• Knowledgeable with 3+ years of relevant industry experience and advanced degree in machine learning, computer science, statistics, biostatistics, mathematics, or related quantitative field
• Proven track record of shipping machine learning-powered algorithm products at B2C-like scale as well as working with cross-functional teams in an agile-like environment
• Your grasp of machine learning fundamentals and ability to design intuitive, working ML solutions in response to complex business problems
• You have a strength in the “design and prototype” part of the ML development pipeline, beginning with pulling datasets from SQL and ending with serializing ML models and assisting engineers to product-ionize model retraining and model serving systems
• When it comes to communicating, you have no problem with ML/algorithm designs clearly to cross-functional team members, especially engineers and product managers
• You are well versed in SQL data warehouses such as Redshift and Snowflake, have worked on current ML tools such as TensorFlow, PyTorch, and Python, and feel comfortable with recommender systems or natural language processing
• To take it one step further, you are effective at translating and blending traditionally distinct ML concepts such as recommender systems, NLP, regression, andиclassification into a common framework such as TensorFlow


Must-have:

От 3 лет опыта разработки ПО с использованием технологии машинного обучения на Python или другом языке программирования
Опыт работы с ML-моделями на всех этапах
Экспертное знание алгоритмов
Знание PyTorch, Tensorflow
Понимание архитектур нейросетей для различных областей (Text-to-Speech, Behavior Prediction, NLP и другие)
Знание английского на уровне B1 и выше


Must-have:
  • 2 years or more of experience in commercial Computer Vision projects;
  • experience with video processing and object recognition on it;
  • experience working with complex, multi-phase projects;
  • good hands-on experience in project architecture creation;
  • development of cross-platform applications.
  • C++/Python;
  • OpenCV.
  • English - upper-intermediate or higher (written and verbal).

Must-have:
  • Computer Vision (object detection, OCR)
  • Image processing (OpenCV)
  • Pytorch
  • Onnx
  • Tensorflow
  • Python

Must-have:
  • Практичний досвід у розвитку Reinforcement Learning, комп'ютер віжен рішень для розробників ігор;
  • Не менше 3-х років досвіду дослідження та розробки алгоритмів машинного навчання;
  • Досвід у розробці табличних даних та часових рядів;
  • Розуміння концепцій та алгоритмів машинного навчання та глибокого навчання;
  • Досвід роботи з бібліотеками та фреймворками (PyTorch, OpenAI Gym, Scikit-learn, XGBoost, TensorFlow тощо);
  • Глибокі знання статистики та лінійної алгебри;
  • Інженерний досвід та великий досвід роботи на Python.

Must-have:

Strong analytical and data interpretation skills
Work experience with Python (Pandas, NumPy, bs4, Selenium, Sklearn, SciPy, Keras)
Experience with scraping and data cleaning
Understating and experience in developing ML algorithms (regression, classification, neural networks )
Strong background in statistics, probability theory, and linear algebra
Good understanding of model scoring, results interpretation, and further usage


Must-have:

• MSc/BSc in Computer Science or similar degree. Knowledge of statistics, probability theory and linear algebra.
• Good knowledge of ML theory and practice — pros & cons of different model types, validation, metrics, hyperparameter tuning, interpretability
• Experience with Tensorflow and Keras (can implement custom NN model from paper)
• Practical experience with ML models in production (2+ years)
• Experience with distributed model training and distributed feature engineering (Spark/Dask/Apache Beam)
• Python 3.х, software engineering skills (able to produce well-structured production-level projects, not only notebook scripts)


Must-have:
  • MS degree in Computer Science or other related fields
  • 3+ years of coding experience with Python
  • A proven track record of R&D projects in ML and/or CV
  • Advanced knowledge and experience in methods for the analysis of time-series data
  • Deep knowledge of such packages as Numpy, Scikit-Learn, Matplotlib, Kats, Sktime
  • SQL Databases + Snowflake
  • Upper-intermediate English
  • Proactivity and good soft skills