R Programmer Trainee null

We are looking for a passionate R Programmer Trainee. The successful candidate will turn data into information, information into insight, and insight into business decisions.

Work with common data structures in R like vectors, matrices, and data frames before expanding your skills by mastering conditional statements, loops, and vectorized functions. You’ll then discover how to optimize your code using code profiling and benchmarking. Finally, you’ll get to grips with writing functions and object-oriented programming (OOP). Be ready to tackle more complex tasks including advanced data visualization and machine learning.

Responsibilities

• Interpret data, analyze results using statistical techniques, and provide ongoing reports
• Develop and implement databases, data collection systems, data analytics, and other strategies that optimize statistical efficiency and quality
• Acquire data from primary or secondary data sources and maintain databases/data systems
• Identify, analyze, and interpret trends or patterns in complex data sets
• Filter and “clean” data by reviewing computer reports, printouts, and performance indicators to locate and correct code problems
• Work with management to prioritize business and information needs
• Locate and define new process improvement opportunities 

Requirements 

• Proven working experience as a data analyst or business data analyst
• Technical expertise in data models, database design development, data mining, and segmentation techniques
• Strong knowledge of and experience with reporting packages (Business Objects etc), databases (SQL, etc), programming (XML, Javascript, or ETL frameworks)
• Knowledge of statistics and experience using statistical packages for analyzing datasets (Excel, SPSS, SAS, etc)
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy
• Adept at queries, report writing, and presenting findings
• BS in Mathematics, Economics, Computer Science, Information Management, or Statistics