Central Health

Sr. Financial Data Analyst

Req No.
2025-9572
Company
Central Health
Job Locations
US-TX-Austin
Type
Regular Full-Time

Overview

The Senior Data Analyst serves as a key contributor to Central Health’s data-driven decision-making, focusing on financial, clinical, and operational analytics. Under general direction of the Analytics Quality Manager, this role organizes, analyzes, and reports on large datasets including claims, financial, actuarial, and enrollment data to support value-based care, cost optimization, and forecasting. This role also supports the development of performance dashboards, data marts, and reporting tools, and plays a critical part in aligning healthcare analytics with actuarial analysis and financial planning. This financial analyst collaborates across clinical, strategy, IT, and finance functions to support strategic priorities with the goal of providing high-quality, equitable care to the people we serve.

 

Hybrid = Individuals in this position may work both at an approved off-site locationand onsite at a primary location or multiple locations based on business needs.

Responsibilities

Essential Functions.

  • Lead the collection, documentation, and translation of business and technical requirements for data analysis and reporting initiatives.
  • Perform descriptive, predictive, and prescriptive analytics to support value-based contracting, forecasting, utilization modeling, and cost-benefit analyses.
  • Develop and maintain advanced reports and dashboards for operational, financial, and clinical stakeholders using
  • SQL, Tableau, and Epic’s analytics suite (RWB, Clarity, Caboodle).
  • Serve as analytics lead on cross-functional projects, including reimbursement modeling, rate setting, and budget impact assessments.
  • Analyze healthcare cost trends, utilization, population risk stratification, and service line profitability in alignment with actuarial methodologies.
  • Conduct sensitivity analyses, cohort comparisons, and scenario planning using statistical and financial modeling techniques.
  • Contribute to the development of internal cost benchmarks, quality-based payment models, and shared savings structures.
  • Support the buildout of the enterprise data warehouse and participate in designing data pipelines, ETL processes, and data governance protocols.
  • Collaborate with finance, operations, planning, and provider teams to provide insights for financial planning, revenue cycle, and payment integrity.
  • Identify, troubleshoot, and resolve data anomalies to ensure data integrity, consistency, and accuracy across systems.
  • Communicate findings through compelling visualizations and executive summaries tailored for both technical and non-technical audiences.
  • Become a data subject matter expert (SME) for the organization’s clinical, financial, and claims datasets.
  • Advanced knowledge of SQL, Tableau, and Python for data extraction, visualization, and modeling.
  • Strong statistical foundation (regression, time series, probability models) with ability to apply these in financial forecasting or risk analysis.
  • Experience analyzing large, complex datasets to support healthcare budgeting, population health strategies, and quality improvement initiatives.
  • Ability to manage and prioritize multiple deadlines in a matrixed organization High
  • Effective communication skills to explain complex analyses to cross-functional stakeholders High
  • Familiarity with healthcare cost structures, pricing, payer-provider relationships, and population.
  • Strong curiosity, attention to detail, and drive to solve complex problems with meaningful impact

Qualifications

MINIMUM EDUCATION:

  • Bachelor’s degree from an accredited university in Finance, Mathematics, Statistics, Economics, Actuarial Science, Engineering, Management Information Systems, or a related quantitative discipline.  

 

MINIMUM EXPERIENCE:

  • 3 years Healthcare, analytics, statistics, economics, public health, or related fields.
  • 3 years SQL (preferably T-SQL) or Python scripting with an advanced level of expertise
  • 3 years MS Excel with an advanced level of expertise
  • 2 years Tableau (or Power BI), Excel, with knowledge of data visualization best practices
  • 2 years Actuarial experience, including forecasting or risk modeling in healthcare
  • 1 year Knowledge of healthcare reimbursement models, population risk, or rate setting

 

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