Current openings at Archive.

The Role We’re looking for a mission-driven Data Scientist to lead development of predictive models, machine learning frameworks, and experimental designs that help us deliver better care and optimize operations. Someone with deep technical expertise and a passion for solving complex problems that make a tangible difference. You will work directly with our CEO and clinical leadership to design data infrastructure, identify actionable trends, and transform raw data into proactive interventions for our clients and care teams. What You’ll Do: Design and deploy predictive models that identify high-risk populations, forecast patient outcomes, and optimize clinical workflows. Use Power BI to design and deploy dynamic, executive-ready dashboards that drive clinical insights, visualize KPIs, and directly inform strategic decision-making at every level of the organization. Apply machine learning techniques (e.g. classification, clustering, regression, NLP) to generate insights from structured and unstructured healthcare data. Lead the design and implementation of scalable data pipelines and infrastructure in collaboration with technical partners. Analyze data across insurance claims, EMR/EHR, patient-reported outcomes, and operational KPIs to support strategic decision-making. Create clean, interpretable visualizations and dashboards to present findings to clinicians, clients, and the executive team. Conduct A/B testing, causal inference, and other statistical evaluations to measure program effectiveness and guide product improvements. Collaborate with clinical teams to define relevant metrics and translate medical workflows into quantifiable signals. Recommend enhancements to our data architecture, tooling, and automation capabilities. Keep Archive ahead of industry trends by monitoring new developments in health data science, data privacy, and healthcare AI. Who You Are: Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field. PhD a plus. 5+ years of hands-on experience applying data science in a healthcare setting. Expertise in Python (Pandas, scikit-learn, NumPy), SQL, and data pipeline tools (e.g. Airflow, dbt, Spark). Strong command of machine learning algorithms, statistical modeling, and data wrangling best practices. Experience working with EMR/EHR systems, healthcare claims, or patient-reported outcomes preferred. Super user of Power BI, Tableau and cloud platforms (e.g. AWS, GCP). Comfortable communicating insights to both technical and non-technical audiences. Passion for healthcare transformation and patient-centered care.