Staff Machine Learning Scientist

Ovii's Interpretation of the Role

The Staff Machine Learning Scientist leads ML strategy for proactive communications, owning end‑to‑end models that decide when, what, and how to nudge members. The role blends deep technical work, rigorous experimentation, and cross‑functional partnership to drive engagement and clinical outcomes.

Role Snapshot

• Lead ML strategy for send‑time and channel optimization
• Own end‑to‑end production models
• Mentor a small ML team
• Drive rigorous experimentation framework
• Collaborate with product, growth, and engineering

Must-Have Requirements

• Python
• SQL
• Machine Learning
• Recommendation / ranking / sequential decision systems
• Experimentation & A/B testing
• ML systems production
• Recommendation / sequential decision systems
• Bachelor's degree in Computer Science, Statistics, Operations Research, Machine Learning, or related quantitative field
• Must have at least a Bachelor's degree in a quantitative field

Nice-to-Have Signals

• Contextual bandits
• Reinforcement learning
• Multi‑objective optimization
• Causal inference
• Cold‑start modeling
• Healthcare data compliance (HIPAA/BAA)
• Hiring and growing a small ML team
• Feature stores (Statsig, Databricks)
• Airflow / dbt
• TypeScript
• Contextual bandits or reinforcement learning
• Causal inference beyond A/B testing
• Healthcare or fintech regulated data
• fintech
• regulated data

Work Setup

• Location: San Francisco, USA
• Work mode: HYBRID
• Remote scope: UNSPECIFIED
• Employment type: Full-Time

Eligibility Gates

• Visa sponsorship: unknown

Not Specified in JD

• Visa sponsorship
• Salary range
• Remote eligibility
• Certifications
• Travel
• Security clearance
• Coding test

What You'll Likely Work On

• Design and ship a send‑time and channel optimization system beyond the current contextual‑bandit approach
• Build and deploy propensity models that balance engagement, fatigue, and unsubscribe risk
• Establish and enforce rigorous experimentation standards (multi‑arm, sequential testing, CUPED, anti‑peeking)
• Own at least one ML model in production from training to monitoring
• Mentor the team’s ML scientists and steer technical direction
• Partner closely with product, engineering, data science, growth and marketing stakeholders

Good Fit If You Have

• Proven track record shipping recommendation or sequential‑decisioning systems end‑to‑end
• Strong expertise in experimentation, causal inference, and multi‑objective optimization
• Experience mentoring or growing a small ML team
• Familiarity with regulated‑data environments such as healthcare or fintech
• Comfort collaborating across product, engineering, and growth functions