UAC Analyst - Mid

Spry Methods•Nashville, TN

About The Position

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.

Requirements

Bachelor’s degree in Data Analytics, Business Administration, Information Technology, Statistics, Mathematics, or a related field from an accredited college or university.
Minimum of three (3) years of experience in data analysis, business intelligence, operational reporting, or a related analytical role.
Experience independently developing and maintaining reports, dashboards, and analytical products for management, customer, or stakeholder audiences.
Experience designing and maintaining performance dashboards and data visualization products using Power BI, Tableau, or similar reporting platforms.
Experience collecting, validating, analyzing, and presenting operational data to support performance monitoring and business decision-making.
Experience working within a service delivery, call center, help desk, or other SLA-driven operational environment.
Experience supporting federal government programs or working within a government contracting environment.
Strong written and verbal communication skills with the ability to present complex data findings to technical and non-technical audiences.
Advanced proficiency in Microsoft Excel, including pivot tables, advanced formulas, charting, and data analysis functions.
Proficiency with Power BI, Tableau, or similar business intelligence and data visualization tools.
Experience using SQL or similar data querying languages to extract, transform, and analyze data from multiple sources.
Familiarity with ITSM platforms such as ServiceNow, Remedy, or comparable ticketing and workflow management systems.
Knowledge of ITIL principles, service delivery metrics, SLA management, and continuous improvement practices.
Experience developing and maintaining data governance artifacts, including reporting standards, data dictionaries, process documentation, and quality controls.
Proficiency with Microsoft Office Suite and collaboration tools including Teams and SharePoint.
Strong organizational skills with the ability to manage multiple priorities, deadlines, and deliverables with minimal supervision.
Experience performing trend analysis, root cause analysis, and developing data-driven recommendations to improve operational performance.
Ability to collaborate effectively with program leadership, operational teams, and cross-functional stakeholders.
Ability to obtain and maintain any required customer security clearance.

Nice To Haves

Active Secret clearance or higher.
ITIL Foundation, ITIL 4, or higher IT service management certification.
Experience using Python, R, or similar tools for advanced data analysis, automation, and reporting.
Lean Six Sigma White Belt, Yellow Belt, Green Belt, or comparable process improvement certification.
certification or experience supporting projects, reporting initiatives, or analytical programs.
Experience working with enterprise data warehouses, ETL processes, or data integration tools.
Familiarity with federal IT governance and compliance frameworks, including FITARA, FedRAMP, and NIST.
Experience supporting quality assurance programs and incorporating customer satisfaction, call monitoring, and performance data into reporting frameworks.
Familiarity with workforce management platforms and call center performance analytics tools.
Experience supporting proposal development through analytical content, capability narratives, past performance writeups, and data-driven solution development.
HDI Support Center Analyst (HDI-SCA) or equivalent service desk or customer support certification.

Responsibilities

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.