Principal Data Analysis

Research, collect, process, and organize data across multiple repositories and business applications. Maintain and update data interfaces, develop data rules and mappings, resolve discrepancies, and analyze data to deliver actionable insights that support business decision-making.

The ideal candidate is a Principal Data Analyst who brings specialized analytical expertise in evaluating complex billing data, identifying trends, and uncovering anomalies across products, systems, customer segments, and transaction flows. This individual will design and implement scalable monitoring solutions that help shift billing assurance from reactive issue resolution to proactive risk identification.

The candidate will play a critical role in reducing revenue leakage, preventing overbilling and underbilling, improving audit readiness, and ensuring billing processes operate as intended. Success in this role requires strong analytical judgment, deep data investigation skills, the ability to connect insights across complex data environments, and experience translating findings into actionable business recommendations.

Key Roles and Responsibilities:

Typical responsibilities may include, but are not limited to, the following:

• Data Collection and Processing: Gather, preprocess, cleanse, and organize data from multiple sources to ensure accuracy, consistency, and readiness for analysis.

• Data Management and Mapping: Maintain and update data repositories, interfaces, data rules, and mapping logic across business applications.

• Data Analysis and Interpretation: Analyze data using statistical and analytical methods to identify trends, patterns, risks, and opportunities. Develop insights and recommendations to support business decisions.

• Reporting and Visualization: Create clear, accurate, and compelling reports, dashboards, and visualizations to communicate findings effectively to stakeholders.

• Discrepancy Resolution and Quality Assurance: Identify, investigate, and resolve data discrepancies across platforms. Support data quality through validation, auditing, and control processes.

• Analytical Tools: Use tools and technologies such as SQL, Power BI, Python, and related analytics platforms to support reporting, analysis, automation, and data management activities.

Recognized as an expert in the field, applying broad business knowledge, technical expertise, and strategic insight to solve complex problems and drive organizational results. Leads critical, high-impact projects and designs or implements innovative business strategies. Works with minimal oversight, regularly consults with senior leadership, and influences executive-level decisions. Serves as a mentor and supports others in resolving complex issues.

Supervisory Responsibility: No

Manages highly complex data storage and integration efforts involving multiple sources. Performs advanced analytics to solve highly complex business problems and deliver strategic business value.

Bachelor’s degree in Computer Science, Mathematics, Data Analytics, Statistics, or a related field preferred. Typically requires 7+ years of related experience. Certification may be required in some areas.