Teradata Data Scientist in Moscow, Russia
We offer working in the most growing and innovative segment of market on biggest data sets using cutting edge technologies for gaining insights from vast amounts and various types of data, incl. traditional data sets, machine logs, sensor data and many more.
You will benefit from knowledge-sharing and support of established data science communities of practice and influenced by the most innovative leaders in big data analytics with international experience from global accounts.
You will tackle the greatest business challenges and unique analytical problems of our clients - and, in particular, those that depend upon non-traditional Analytics (like path, graph and time-series Analytics) and/or non-traditional data (like weblog and machine-log data).
Clarify and translate business problems into technical requirements and design analytical solutions using various data science / advanced analytics / data mining techniques.
Work closely with client teams to generate insights, diagnose problems, and provide information for business and product decisions by transforming very large data sets into actionable information.
Perform both regular and ad-hoc analysis leveraging a wide array of data tools and techniques from open source to proprietary.
Interpret and document the analysis and results and communicate the information effectively to the client.
Actively participate on knowledge sharing process within the regional analytics team and the entire company.
Exploration: Base skills in statistics, algorithms, machine learning, and mathematics. A solid grounding in these principles is required to actually extract signals from the data and build solution with it.
Communication: Making the results real by making data available to users. This involves communicating the results of analysis clearly and effectively to both business and technical users in presentations. Lead the discussion and guide the integration of the data visualization layer with the underlying platform to best showcase the output of the data. Upper-intermediate English language
Flexibility: Ability to work effectively as a real team player, ability to collaborate with international teams
Experience: 3 years of experience on relevant analytical projects with consultancy characteristics. Familiarity with large data sets and distributed computing based on MapReduce principles (e.g. Hadoop, Spark, Hive, Pig, Teradata Aster, etc.), familiarity with SQL and experience with at least one programming language, preferably R, Java, Python or Scala. While advanced coding techniques are not required, the candidate needs to be aware of the open source libraries and packages available.
PhD/Masters/bachelor's degree in Statistics or Computer Science, and / or relevant work experience is a plus
Knowledge of analytical toolsets, such as SPSS, SAS etc. is a plus.
Knowledge across multiple industries is a plus.
Ability to initiate and drive analytical/data science projects to completion with minimal guidance is a plus.
Ability to innovate, to creatively design solutions and to automate processes is a plus.
Knowledge of Architecture Principles, Design Patterns, and Implementation Alternatives in big data analytics environments is a plus.