Data Analyst

Summary:

The Data Analyst supports PBACO’s value-based care and operational objectives by producing accurate, timely, and actionable reports and analyses using data assets maintained by the company and population health partners. This role focuses on delivering analytics that directly support initiatives with measurable return on investment (ROI), including cost savings, revenue protection, quality improvement, and operational efficiency. The Data Analyst executes reporting and analytic work under established standards, policies, and protocols, ensuring insights are not only correct but usable. The role partners closely with Senior Data Analyst and internal stakeholders to clarify requirements, highlight opportunities tied to outcomes, maintain documentation, and continuously improve efficiency across reports, projects, and processes.

ESSENTIAL DUTIES AND RESPONSIBILITIES

Reporting & Analytics Execution

- Build, maintain, validate, and refresh recurring reports and dashboards (Excel, SQL, Power BI, Python) strictly according to the approved reporting schedule and calendar.
- Ensure reports are
actionable
, clearly tied to operational, clinical, financial, or quality initiatives, and structured to support decision-making.
- Produce accurate, complete, and executive-ready outputs that align with defined metric definitions, sources of truth, and initiative goals.
- Highlight trends, variances, and outliers that indicate
opportunity, risk, or ROI impact
(e.g., cost avoidance, revenue opportunity, quality improvement).
- Escalate findings, data concerns, or logic questions to Senior Data Analyst or others as appropriate.

Ticket Management & Request Intake

- Review and accept assigned data tickets within
2 business hours
of assignment.
- Proactively ask clarifying questions of the requestor to confirm scope, definitions, timelines, and expected outputs before beginning work.
- Follow Data Team intake, prioritization, and communication protocols for all assigned tickets and ad hoc requests.

- All tickets and assigned projects will be prioritized and assigned a
Level (I, II, or III)
by department managers based on:
- Complexity
- Business priority
- Required skill set
- Availability of team members
- SLA levels are
subject to change
based on evolving business needs.

Assignment/Ticket Resolution Targets

- Level I:
Resolved within 24 business hours
.
- Level II:
Resolved
within
2–4 business days
, depending on priority.
- Level III:
Resolved within 4–5 business days
.
- Analysts are responsible for
end-to-end ownership
, including:
- Following up with the requestor
- Coordinating with validators
- Ensuring final delivery is accurate, actionable, and clearly communicated.

\*Resolved means plan created, result drafted, validated, approved, communicated and accepted.

Timeliness & Reliability

- Deliver assigned reports, tickets, and analyses in accordance with the formal reporting schedule and the defined
ticket SLA levels (I, II, III)
, ensuring timely resolution, validation, and communication.
- Manage work to ensure validation is completed within reporting timelines without compromising accuracy.
- Communicate early and clearly when risks to timelines, data availability, or validation outcomes are identified.

Data Validation & Quality Control

- Validation is a core and critical responsibility of the Data Analyst role.
- Execute all required validation checks (reconciliations, cross-source comparisons, variance thresholds, historical trending, and peer review)
for every report and deliverable
prior to release.
- Confirm report accuracy, completeness, and reasonableness before distribution; no report is considered complete until validation is finalized.
- Clearly document validation steps, findings, and sign-offs in accordance with Data Team standards.
- Immediately escalate validation failures, unexplained variances, or suspected data integrity issues.
- Support root-cause analysis for identified data issues and implement corrective and preventive actions as directed.

Documentation & Standards

• Maintain accurate and up-to-date documentation, including metric definitions, SOPs, job aids, and knowledge-base articles, for assigned reports and processes.
• Adhere to Data Team policies, data governance standards, naming conventions, and company-wide compliance requirements.