Data and Analytics Support

We are looking for a detail-oriented and analytical Data & Analytics Support Contractor to assist in assessing the integrity, reliability, and future-state requirements of PG reporting. This role involves acquiring and preparing data from complex operational and reporting platforms, performing reconciliations and targeted testing, analyzing policy- and plan-level trends, validating effective dates and mappings, and translating technical findings into clear, actionable insights for cross-functional business and executive stakeholders. The successful candidate will collaborate closely with teams across PG Reporting, Business, Technology, Operations, Workforce, Risk, Control, and Quality to differentiate isolated data anomalies from systemic reporting risks, while developing traceable analysis, reusable calculation logic, and comprehensive documentation for long-term ownership.

Key Responsibilities

Data Discovery & Preparation:
Work with assessment leads and subject-matter experts to translate business questions, policy requirements, and reporting risks into executable analysis plans. Identify, extract, combine, and prepare data from various sources including VQ inventories, Atlas records, dashboards, reconciliation files, source systems, volume reports, and prior issue documentation. Document data availability, ownership, business definitions, lineage, quality considerations, assumptions, and limitations.

Data Quality, Reconciliation & Validation:
Assess data completeness, accuracy, consistency, lineage, timeliness, and fitness for purpose across primary operational and reporting systems. Conduct multi-source reconciliations involving source data, policy-to-VQ mappings, customer eligibility, effective dates, operational reports, client dashboards, and executive reporting. Design and perform targeted sampling to reproduce key metrics, validate corrected records, and confirm remediation effectiveness. Evaluate changes in VQs—including new, modified, consolidated, or sunset versions—to understand their impact on mappings, metrics, customer populations, and downstream reporting.

Trend Analysis & Risk Identification:
Analyze plan-level contact volumes and performance trends against historical baselines (month-over-month and year-over-year) to detect unusual shifts, outliers, and potential routing or reporting anomalies. Quantify the scope, severity, and business impact of findings, clearly documenting assumptions and unresolved gaps. Prioritize analytical efforts based on materiality, customer impact, risk recurrence, and value to executive decision-making.

Reporting, Recommendations & Operationalization:
Translate complex data findings into concise visualizations, executive summaries, and actionable recommendations. Develop repeatable analytical routines, including SQL queries, calculation logic, metric definitions, monitoring thresholds, and data quality checks. Support evaluations of future-state source options, data models, reporting architecture, automation opportunities, and policy-specific attribution models. Maintain organized analysis files, validation evidence, source-to-report lineage, and supporting documentation. Assist with post-assessment activities such as data remediation, dashboard development, user acceptance testing, and production monitoring.

Required Qualifications

Education:
Bachelor’s degree in Analytics, Data Science, Information Systems, Business, Finance, Operations, or equivalent practical experience.

Experience:
Minimum of 5 years in data analysis, business intelligence, reporting, data quality, or operational analytics.

Reconciliation Expertise:
Demonstrated ability to reconcile complex, multi-source datasets and identify root causes of reporting variances.

Technical Proficiency:
Strong skills in SQL and advanced Excel, with experience in enterprise BI and visualization tools such as Power BI or Tableau.

Analytics Foundation:
Proven experience defining metrics, writing calculation logic, validating effective dates and mappings, and testing reporting outputs.

Problem-Solving & Communication:
Exceptional analytical judgment with the ability to structure ambiguous queries. Excellent written and verbal communication skills to effectively present technical findings to non-technical audiences.

Cross-Functional Collaboration:
Proven success working across business, technology, operations, risk, and control teams under tight deadlines.

Preferred Qualifications

Experience in healthcare, pharmacy, contact-center, customer service, or regulated operational reporting environments is highly desirable. Familiarity with data lineage, master/reference data management, single-source-of-truth design, governance, and data quality controls is a plus. Experience analyzing routing, queue, vendor, contact-volume, eligibility, or policy-level data structures is beneficial. Knowledge of advanced analytics tools such as Python, R, Alteryx, Databricks, or cloud data platforms is preferred.