Commence is seeking to solve the problem of data-centric transformation in healthcare to elevate health outcomes and power more efficient processes for program and patient health.
Requirements
- Bachelor’s degree in Health Informatics, Public Health, Statistics, Computer Science, or a related field
- 3+ years of experience working with healthcare data, including EHR, claims, or public health data
- Strong proficiency in SQL and at least one analytics-oriented language (e.g., Python, R)
- Experience with data analysis and visualization tools such as Excel, Tableau, Power BI, or Quicksight
- Familiarity with healthcare data standards (e.g., FHIR, HL7, ICD, CPT, LOINC) and common quality or performance measures
- Experience working in a healthcare or regulated environment
- Experience with Agile development methodologies
Responsibilities
- Analyze and interpret large-scale healthcare datasets (e.g., claims, EHR, FHIR, registries) to identify trends, outliers, and key performance indicators
- Collaborate with data engineers, product managers, and domain SMEs to define data requirements, metrics, and quality controls
- Build and maintain curated datasets and dashboards for internal and external stakeholders using SQL, Python, or BI tools
- Support design and execution of analyses for clinical, operational, or policy use cases, including cohort definitions, utilization patterns, and risk stratification
- Develop and document business rules for data standardization, mapping, and transformation
- Assist in data validation and QA efforts for data pipelines and analytics-ready datasets
- Ensure data privacy and compliance with HIPAA, 42 CFR Part 2, and organizational security protocols
Other
- Bachelor’s degree in Health Informatics, Public Health, Statistics, Computer Science, or a related field
- Excellent communication and collaboration skills, with the ability to work effectively with both technical and non-technical teams
- Strong problem-solving skills, attention to detail, and a passion for continuous learning
- Ability to synthesize complex data and present findings to technical and non-technical audiences
- Detail-oriented with strong data hygiene, validation, and documentation habits
