Data Scientist

Published on Jul 13, 2021

An Outstaff company with office in Kyiv, Ukraine.

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3-5 years
Job Type:
Data Engineering
Deep Learning
Data Science & AI

What You Will Do Responsibilities
  • Study new data sources and find insights/correlations to investigate how data can be used to solve new business challenges.
  • Create prototypes with data sets and provide guidance on leveraging and combining new data sources for new business insights.
  • Apply statistical analysis and modelling techniques on small and large datasets to solve specific business problems in diverse industrial domains.
  • Provide strategic leadership in selection of platforms, tools, techniques and processes in the practice of the data science discipline.
  • Collaborate with product owners / product managers from other business units and/or customers to translate business requirements into algorithmic requirements that can be implemented with statistical and machine learning techniques.
  • Provide mentorship to other data scientists in the team.
  • Own and drive contemporary best practices in applying and deploying data science at scale.
  • Participate in designing the data architecture.
  • Process, cleanse and verify the integrity of data used for analysis.
  • Execute analytical experiments methodically.

What You Should Bring
  • Advanced degree (Ph.D. preferred) in engineering, science, mathematics or related subjects
  • Expert knowledge of statistical programming languages such as R or Python, and SQL.
  • Readiness to work with engineering teams to develop prototypes of software products leveraging exploratory data analytics.
  • Expert knowledge of data visualization, using tools such as Tableau or PowerBI.
  • Expert knowledge of Experimental Design and Statistical Decision Theory.
  • Solid knowledge of distributed data storage and computing, including Hadoop or Cassandra.
  • Practical knowledge of cloud computing, including AWS (preferred) or Azure and highly scalable databases, such as Dynamo DB.
  • Knowledge of NoSQL databases, such as MongoDB.
  • Great communication skills in English.
  • 5+ years working and communicating with business stakeholders as a trusted adviser in data science.
  • 5+ years translating business requirements into data science problem statements and execution tasks.
  • In-depth understanding of the machine learning lifecycle.
  • Practical skills with agile software development methods such as Scrum and Kanban
  • Experience in executing advanced analytics for customers, including marketing mix analysis, segmentation, retention modelling, targeted marketing, basket analysis, next product recommendation, and so forth.
  • Experience with color science.

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