10 days ago
Responsibilities
- Design, train, and validate predictive and statistical models for healthcare data.
- Frame business questions as modeling problems and define success metrics.
- Engineer features and conduct applied research on various datasets.
- Own the full model lifecycle from exploratory analysis to post-launch monitoring.
- Collaborate with product managers to translate customer problems into product features.
- Provide technical leadership and mentorship on statistical and ML methodologies.
- Document models and assumptions for interpretability and reproducibility.
Requirements
- 6+ years of experience in machine learning roles with production model deployment.
- Strong foundations in applied statistics and machine learning techniques.
- Experience with agentic tools and a commitment to pushing development boundaries.
- Ability to communicate technical concepts clearly to non-technical audiences.
- Hands-on experience with messy, real-world datasets.
- Proficiency in SQL and collaboration with data engineers on production pipelines.
- Fluency in Python's data and ML stack.
Benefits
- Ground floor opportunity in a high-growth startup with world-class investors.
- Reimbursements for relevant learning and up-skilling opportunities.
- Full-remote flexibility with a work-from-home stipend.
- Generous time off and flexible hours.
- 100% paid health, dental, and vision plans for employees.
- $1,000 home office stipend for remote equipment.
- Optional team retreats for co-working and social gatherings.
- 8-16 weeks of fully-paid, flexible parental leave.