Data Analyst

Job Requirements

• Bachelor’s of Science or Arts Degree in Business Management, Supply Chain Management or related field from an accredited college or university
• Additional five (5) years+ of prior military, Department of Defense or related business experience related to data management
• Three (3) years+ experience with coding skills in languages such as SQL, Python and/or R
• Analytical and problem-solving skills
• Experience with statistical software (e.g., Stata, SPSS)
• Knowledge of data gathering, cleaning and transforming techniques
• Reporting and data visualization skills using software like Tableau
• Understanding of data warehousing and ETL techniques
• Proficiency in Microsoft Excel
• Favorably adjudicated PSI at a T3 level

Qualifications

Strategic Technology Institute, Inc. (STi) is seeking qualified applicants for a Data Analyst position supporting Naval Sea Systems Command’s (NAVSEA) Naval Surface Warfare Center Carderock Division (NSWCCD) requirements at their research facility in Bethesda, MD.

STi is a minority-owned small disadvantaged business (SDB) providing effective and innovative solutions in Maintenance, Repair, & Overhaul (MRO), logistics, Safety, Reliability, Maintainability, & Quality Assurance (SRM&QA), IT & cybersecurity, and project management & control.

The management system is AS9100D-certified, ISO 14001:2015-certified, and ISO 9001:2015-certified with respect to business management and program management, which deeply influences our consistent “Safety First, Quality Always” culture.

Responsibilities

Operations research analysts help determine better ways to coordinate and manage large organizations that require the effective use of money, materials, equipment, and people. This is accomplished by applying analytical methods from mathematics, science, and engineering.

Analysts gather information, then select the most appropriate analytical technique. Analysts can use any of several techniques, including simulation, linear and nonlinear programming, dynamic programming, queuing and other stochastic-process models, and the analytic hierarchy process.

The use of models enables the analyst to assign values to the different components and clarify the relationships among them. The values can be altered to examine what may happen to the system under different circumstances.