Onos Health is addressing the 30% of total U.S. healthcare spending wasted due to ineffective care and administrative burden caused by misalignment between providers and payers by building the largest AI-driven healthcare data platform.
Requirements
- Deep expertise in statistical modeling, causal inference, and ML (Python, SQL, and related libraries such as scikit-learn, statsmodels, PyTorch, or similar).
- Familiarity with healthcare data standards (claims, eligibility, EHR/clinical data, coding sets like ICD, CPT, HCPCS)
- Experience building production-grade models and deploying them in analytical or product environments.
Responsibilities
- Design and deploy predictive, risk-scoring, and optimization models that identify waste, inappropriate utilization, and care improvement opportunities across behavioral health services.
- Help define and evolve our data science stack, from feature stores and pipelines to model monitoring and evaluation frameworks.
- Dive deep into claims and clinical data to uncover trends, outliers, and actionable insights.
- Partner with client teams to translate complex models into clear insights that demonstrate ROI, inform payer workflows, and maintain clear, impactful dashboards.
- Collaborate with the CEO, CPO, and engineering team to guide product direction, data strategy, and key client engagements.
Other
- 8+ years of experience in data science or advanced analytics (preferably in healthcare or health plans; experience with claims and clinical data strongly preferred).
- Proven experience building, mentoring, and leading high-performing data science or analytics teams.
- Scrappy with an entrepreneurial mindset: resourceful, proactive, thrives in ambiguity, and moves fast
- Excellent communication skills an ability to translate complex data into clear business insights
- Exceptional references from colleagues and former managers
