Data & Reporting Analyst

The Data & Reporting Analyst is responsible to gather, clean, model, interpret and present data. They must research and use data to solve problems, optimize profit, minimize turnover, or streamline logistics, and to help make business decisions. It is their responsibility to assess the Facilities Team’s complex information with the goal of reaching simpler, smarter conclusions, and use their technical expertise to stress test the data for quality and accuracy.

Essential Responsibilities:

• Collect and analyze relevant data to identify trends, patterns, and areas for improvement
• Perform statistical analyses on large sets of data
• Perform regular backups to ensure data preservation
• Evaluate internal systems for efficiency, problems, and inaccuracies, and develop and maintain protocols for handling, processing, and cleaning data
• Contribute to data dictionary, standards, training, and ongoing updates
• Develop and execute a regional business plan aligning with program goals
• Help identify the business data needed to produce the most useful insights and future analytics
• Monitor data management processes to ensure data quality and consistency
• Prepare written and visual materials for supervisors’ use including spreadsheets, PowerPoint presentations, and reports.

Additional Responsibilities:

• As assigned by Director or Senior Manager

Specific Knowledge, Skills and Abilities:

• Excellent written and verbal communication skills
• Strong SQL or Excel skills, with aptitude for learning other analytics tools
• Technical writing experience in relevant areas, including queries, reports, and presentations
• Strong critical thinking skills and attention to detail
• Proven ability to handle confidential information with discretion, be adaptable to various competing demands in a high paced environment
• Deadline-oriented

Preferred Education, Experience and Licenses:

• Bachelor’s degree in mathematics, computer science, economics, or statistics
• Solid 5 years’ of practical experience in statistical analysis through the use of statistical packages, including Excel, SPSS, and SAS
• Experience with database and model design and segmentation techniques