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Must-have:

— Strong knowledge of Python (numpy, pandas, scikit-learn, etc.);
— Experience with big data technologies;
— Experience with at least one DL frameworks (Tensorflow, PyTorch);
— Experience in developing model from scratch (problem definition, data collection, feature engineering, model selection, validation, tuning, etc.);
— Deep understanding of classical ML Algorithms;
— Good knowledge of math and statistics;
— Good knowledge of PostgreSQL, MS SQL.


Must-have:
  • Experience as a Data Scientist or Data Analyst more than 2 years,
  • Experience in data mining,
  • Understanding of machine-learning and operations research,
  • Knowledge of SQL and Python,
  • Analytical mind and business acumen,
  • Strong math skills (e.g. statistics, algebra),
  • Problem-solving aptitude.

Must-have:

— The ability to perform all stages of Machine Learning services development — from data collection to production deployment
— Experience in data preparation, data normalization, and feature engineering for Machine Learning
— Advanced level in TensorFlow and Keras
— Experience in Data Science
— Experience in programming on Python
— Strong math background for Machine Learning and Data Science
— Experience in data collection from different data sources (SQL databases, third-party services)
— Experience with SQL databases (PostgreSQL / MS SQL / MySQL)


Must-have:

• Ph.D. or Master’s Degree in Computer Science or related field
• Practical experience and extensive knowledge in Applied Statistics and Data Mining to identify hidden patterns in data, evaluate current data flow, or develop a new one
• Strong communication and presentation skills, including translation of complex concepts in clear, concise, and meaningful ways, that non-technical audience can easily understand
• Strong knowledge of SoTA in Machine Learning, Deep Learning, and their application to solving complex problems
• Expertise in more than one Data Science Specializations such as NLP, Time Series Analysis, CV, Recommender Systems, and others
• Understanding of Machine Learning operationalization processes
• Experience in working on complex projects where independent judgment is used within a broad range of defined procedures and practices
• Comprehension of the concept of Software Development Life Cycles of AI projects
• Upper-intermediate English level or higher
• Knowledge in Big Data solutions and advanced data tools in Cloud Platforms
• Hands-on experience in building and operationalizing machine learning models, including data manipulation, experiment design, developing analysis plans, and generating insights
• Advanced proficiency in programming software such as Python, R, C++, Scala, and others
• Strong interpersonal, analytical, and problem-solving skills to lead teams of data scientists and software engineers to successful project execution

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