We are looking for a passionate and certified Data Analyst. The successful candidate will turn data into information, information into insight, and insight into business decisions.
Data analyst responsibilities include conducting full lifecycle analysis to include requirements, activities, and design. Data analysts will develop analysis and reporting capabilities. They will also monitor performance and quality control plans to identify improvements.
- 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.
- Proven working experience as a Data Analyst or Business Data Analyst.
- Technical expertise regarding data models, database design development, data mining, and segmentation techniques.
- 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.
- Master’s degree in Statistics/Data Sciences/or equivalent.
- Demonstrated work history of quantifying field data and presenting the same to a formal setting.
- 3-5 years of relevant working experience.
- Good Analytical and IT skills are mandatory.
- Excellent Business Communication and Interpersonal skills.
- Structured Query Language (SQL).
- Microsoft Excel.
- Critical Thinking.
- R or Python-Statistical Programming (optional).
- Data Visualization.
- Machine Learning.