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Job Opportunity: Data Analyst

Date   Sep 19
Listing No.   IE260119
Sector   Hi-Tech, Technology & IT
Region   North
City/Yishuv   Misgav
Data Analyst
The company stands at the very cutting edge of the Big Data revolution, incorporating innovative technologies and the latest generation of analytical tools in order to deliver unparalleled services and technical support. In order to maintain our technological edge, we are searching for a talented data analyst to join our Analytic team. Our ideal candidate is highly skilled and experienced in all aspects of data analytics, able to transform trends into readable, goal-driven reports for continued innovation and business growth.

Responsibilities & Scope

Develop, implement, and maintain leading-edge analytic systems, taking complex data sets and building simple frameworks.
Identify trends and opportunities for growth through analysis of complex data sets.
Evaluate organizational methods and provide source-to-target mappings and information-model specification documents for data sets.
Create best-practice reports and actionable insights based upon data mining, analysis, and visualization.
Evaluate internal systems for efficiency, problems, and inaccuracies, developing and maintaining protocols for handling, processing, and cleaning data
Work directly with management and departmental managers in order prioritize business and information needs.


Skills and Qualifications

Bachelor’s degree in Mathematics, Computer Science, Economics, or Statistics.
3+ years experience in mining data as a data analyst.
Proven analytic skills, including mining, evaluation, analysis, and visualization.
Technical writing experience in relevant areas, including queries, reports, and presentations.
Strong SQL or Excel skills with the ability to learn other analytic tools.

Additional Preferred Requirements

Prior experience with database, model design and segmentation techniques.
Strong programming experience with frameworks including XML, JavaScript, and ETL.
Practical experience in statistical analysis through the use of statistical packages including Excel, SPSS, and SAS.
Proven success in a collaborative, team-oriented environment.
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