Top Healthtech Data & Analytics Jobs

Analyzes nursing workforce trends, staffing capacity, labor utilization, turnover, absenteeism, and leave activity. Develops dashboards, reports, workforce forecasts, staffing models, and capacity-planning analyses. Partners with nursing, HR, Finance, Staffing, and Talent Acquisition leaders to identify workforce risks, recommend staffing strategies, improve resource allocation, and support data-driven decisions. Ensures workforce data accuracy and standardizes metrics, reporting methodologies, and analytical processes.

Analyze clinical data completeness, reliability, and effectiveness across healthcare facilities, vendors, interoperability networks, and integration pathways. Reconcile claims with clinical records, identify missingness and latency, report ADT coverage, evaluate data technologies, recommend vendor configurations, and prioritize facilities for direct acquisition. Partner with product, engineering, and clinical teams to improve scalable, trustworthy data pipelines and support TEFCA and QHIN strategy.

Own the company-wide BI strategy, infrastructure, governance, dashboards, LookML models, forecasting, and analytics request process. Partner with executives, business owners, Data Engineering, Product, and Engineering to improve data reliability, translate business questions into recommendations, and surface trends and opportunities. The role requires SQL, BI tooling, and data warehouse expertise, with Python, predictive modeling, and statistical analysis preferred.

Build and maintain scalable dbt-based data models and analytics-ready datasets for pharmacy benefit management and care navigation. Translate healthcare workflows into auditable data products, implement data quality testing and reconciliation, optimize warehouse performance, and establish documentation, lineage, governance, CI/CD, and observability practices. Collaborate with technical and business teams to support reporting, financial analysis, self-service BI, and future AI-enabled analytics capabilities.

Leads end-to-end healthcare payer data conversions between platforms, including profiling, transformation mapping, ETL design, mock and parallel runs, bulk loading, validation, testing, defect resolution, documentation, and client reporting. Develops Python and SQL conversion routines, manages risks and timelines, collaborates with onshore and offshore teams, and mentors junior staff. Requires expertise in claims, enrollment, or provider data and extensive technology integration leadership.

Develops scalable data models, Databricks pipelines, backend applications, ETL processes, and data ingestion systems. Partners with engineering, product, and business stakeholders on technical roadmaps; monitors and optimizes data systems for performance, reliability, and scalability. Provides technical leadership, mentors junior engineers, conducts code reviews, and builds secure solutions for sensitive healthcare data.

Leads the Analytics Systems Team of 6–10 engineers, overseeing team development, engineering quality, project delivery, product direction, roadmap prioritization, and strategic analytics infrastructure. The role guides development of data pipelines, analytics tooling, feature stores, and foundation-model integrations supporting clinical trials, diagnostics, biomarker discovery, and regulated Life Sciences workflows.

Administers and optimizes the HRIS, including configuration, upgrades, integrations, troubleshooting, and data governance. Develops standard and ad hoc reports, KPI dashboards, regulatory reports, and employee survey outputs. Analyzes workforce data to identify trends, recommend improvements, and support strategic decisions. Partners with vendors and IT on system enhancements while ensuring data integrity, privacy, and operational efficiency.

Manages and prepares data from internal and external sources, validates data quality, performs descriptive, predictive, and prescriptive analysis, and documents methodologies and outcomes. Develops and maintains self-service reporting tools and dashboards, supports regular and ad hoc reporting, trains customers, and presents audience-appropriate findings. Identifies anomalies, investigates root causes, ensures reproducibility, and provides recommendations to support data-driven underwriting and actuarial decisions.

Build and maintain modern data-centric applications, pipelines, transformations, enrichment processes, provisioning layers, and user interfaces supporting clinical and operational healthcare processes. Analyze clinical data and report trends using cloud, big data, data science, and modern software development practices. Collaborate with Product, Platform, and Architecture teams, mentor Data Engineers, document solutions, manage source control, and research emerging technologies.