Staff Data Scientist (Healthcare)

Location: Fully remote, available only to candidates in AZ, CO, FL, GA, ID, IL, KS, MA, MI, MN, MO, NH, NY, NC, OH, OR, PA, SC, TN, TX, UT, VA, WA, or WI

Salary: $190,000–$220,000 base salary per year

Company

hirify.global is a healthcare software-as-a-service company providing technology for healthcare providers, clinicians, and patients, including education, care workflows, clinical pathways, remote therapeutic monitoring, and outcomes collection.

What you will do

• Design, develop, validate, deploy, monitor, and retrain predictive and risk-adjustment models, beginning with outcomes benchmarking.
• Set methodological standards for statistical modeling, validation, documentation, and responsible use of healthcare data.
• Write tested, versioned, reviewed, and reproducible production code and deploy models in Snowflake with Data Engineering.
• Evaluate how products, programs, and content affect patient outcomes using experimental and observational methods.
• Translate ambiguous product and clinical goals into well-defined modeling problems and ship solutions with product, engineering, clinical, and customer-facing teams.
• Establish practices for model evaluation, monitoring, documentation, and trustworthy use of healthcare data.

Requirements

• Demonstrated ownership of production models through deployment, monitoring, and retraining.
• Strong statistical reasoning, including data-generation processes, model assumptions, uncertainty, and method selection.
• Strong Python and SQL skills with disciplined software engineering, including testing, version control, code review, and reproducible pipelines.
• Experience with messy real-world healthcare data, causal inference, and evaluation design.
• Experience taking open-ended business goals through to shipped product features in partnership with product and engineering teams.
• Degree in statistics, biostatistics, computer science, economics, or another quantitative discipline, or equivalent demonstrated capability.

Nice to have

• Experience with patient-reported outcomes, risk adjustment, outcomes benchmarking, EHR/EMR data, or claims data.
• Experience building recommendation systems and measuring adoption and downstream impact.
• Experience evaluating generative AI applications in regulated healthcare environments.
• Model documentation or validation that has passed diligence, audit, regulatory, or peer review.
• Experience as the first data science or machine learning hire.

Culture & Benefits

• Remote-first working environment with a mission focused on improving patient health and reducing the cost of care.
• Multidisciplinary collaboration across product, engineering, clinical, customer-facing, and leadership groups.
• Values centered on excellence, fortitude, service, responsible decision-making, and continuous improvement.
• Opportunity to shape the first dedicated data science practice and establish modeling standards.