Company Overview
Spry Methods is a proven provider of mission-focused technology, cybersecurity, and program management solutions supporting critical Federal missions. We specialize in delivering integrated, high-impact solutions across cyber operations, enterprise resource management, and mission support services. Our culture emphasizes collaboration, accountability, and innovation - empowering our teams to deliver meaningful outcomes in complex, high-security environments.
The Mid-Level Data Analyst plays a key role in supporting the performance monitoring, reporting, and continuous improvement efforts of the IT Call Center program. This position is responsible for developing and maintaining analytical products, evaluating operational performance data, and delivering actionable insights that support service delivery, customer satisfaction, and data-driven decision-making. Working closely with program leadership, operations managers, and stakeholders, the Mid-Level Data Analyst helps ensure reporting accuracy, identifies performance trends, and supports strategic initiatives that drive operational excellence. The ideal candidate is an analytical problem-solver who thrives in a fast-paced environment, enjoys turning data into meaningful insights, and is passionate about using information to improve business outcomes and customer experience.
As a Mid-Level Data Analyst, you will:
-
Collect, analyze, and validate operational data from ITSM platforms, telephony systems, workforce management tools, and other program data sources.
-
Design, develop, and maintain dashboards, scorecards, and reports that provide visibility into call center performance, service levels, customer satisfaction, and operational trends.
-
Monitor daily, weekly, and monthly performance metrics, identify trends and anomalies, and provide actionable recommendations to program leadership.
-
Prepare recurring and ad hoc reports, performance reviews, executive briefings, and customer-facing deliverables.
-
Conduct root cause analysis of performance gaps, SLA impacts, and operational challenges to support informed decision-making.
-
Support continuous improvement initiatives through data analysis, performance monitoring, and process optimization recommendations.
-
Develop and maintain data governance standards, reporting templates, data dictionaries, and analytical documentation to ensure reporting accuracy and consistency.
-
Partner with supervisors, team leads, and operations managers to validate data, resolve reporting discrepancies, and improve data quality.
-
Perform workforce management analysis, including staffing trends, schedule adherence, forecasting, and capacity planning.
-
Support operational reviews and customer briefings by presenting analytical findings and responding to stakeholder questions.
-
Provide mentorship and guidance to junior analysts, sharing best practices and supporting professional development.
-
Maintain reporting configurations, data extraction processes, dashboards, and supporting analytical infrastructure.
-
Analyze quality assurance results, call monitoring data, and customer feedback to identify improvement opportunities and support coaching initiatives.
-
Respond to stakeholder data requests with accurate, timely, and well-presented analytical products.