Data Scientist - Manager

Company Name: EY
Location: Dubai
Date Posted: 04th Apr, 2017

Role and Responsibilities -

  • Clear understanding on how data analytics will impact business operations and the benefits of applying it;

  • Understanding of region demand on data and data analytics;

  • Have deep experience on development of statistical models on predictive sciences using different techniques(R programing – regression, Raroc, etc)  and tools (SAS, SPSS, Hadoop, etc);

  • Develop decision analytics solutions using new methodologies and techniques that will bring innovation to the region in terms of analytics;

  • Curiosity about data including customer data and market data;

  • Develop white papers on the analytical space helping on positioning and branding;

  • Have a track record of building predictive analytics for different sectors not only in the TAS service line;

  • Provide counselling and mentoring support to the team members;



Key competencies

  • Knowledge of Decision Analytics techniques;

  • Solid understanding of Data Strategy , including data structure, data organization and access;

  • Strong academic record; ideally a professional qualification, Master’s degree, MBA or PhD, from reputable institutions. Financial, Business, Economic, Computer Science, Operations Research, Business Analytics, Statistics, Mathematics, Physics, Engineering or similar degrees are a significant advantage.

  • Strong Analytics knowledge, including tools (SAS, SPSS, R, Hadoop) and methodologies;

  • Excellent problem solving, project management, facilitation and interpersonal skills

  • Team player with the ability to build effective relationships at all levels

  • Willing and able to travel across the region  0-35% of the time


  • Approximately 7+ years of data analytics and decision analytics

  • The professional has to have experience in delivering decision analytics / Operations Research solutions based on techniques which could include some of the following:

    • Operations Research (simulation, optimisation, scheduling, inventory control, queuing theory, risk analysis, decision analysis, system dynamics, etc)

    • Statistics (e.g. price elasticity analysis, forecasting, predictive analytics)

    • Data mining, data visualisation and data management

    • Database modelling including use of emerging Big Data technologies(Hadoop)

    • Experience of analytics packages, including statistics packages such as SPSS or SAS, visualisation packages such as Tableau or Spotfire

    • Strong knowledge of SQL and relational databases, as well as knowledge of predictive modelling technologies such as SAS Enterprise Miner, SQL Server 2005 DMX etc

  • Technically competent in the following areas: data collection and load, data quality assessment, data cleansing, complex data transformation, relationship profiling, sampling and extrapolation, statistical modelling, segmentation, structured data mining, text mining and analytical matching

  • Has strong IT skills to programmer level, covering a range of different technologies relating to the techniques above