Data Scientist (NLP); ID 68891

Published on Aug 23, 2021

An Outsource company with offices in Kyiv, Ukraine; Lviv, Ukraine; Kharkiv, Ukraine; Odessa, Ukraine; Dnipro, Ukraine; Zaporizhzhya, Ukraine.

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

What You Will Do Responsibilities

• Full-stack Data Analysis, Deep Learning, and Machine Learning models pipeline includes deep analysis of customer data, modeling, and deployment in production. It also includes decision-making regarding relevant computational tools for study, experiment, or trial research objectives
• Production of clear, concise, well-organized, and error-free computer programs with the appropriate technological stack
• Presenting results directly to stakeholders and gathering business requirements
• Compiling and interpreting analysis results as well as contributing to the proposals and architecture vision delivered to the customer

What You Should Bring

• 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
• Suitable 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
• Understanding 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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