Member of Technical Staff - Data Analysis

This role owns the analytics spine of HugClaim. You will convert noisy product and model behavior into high-confidence evidence, then drive decisions across quality, safety, and business outcomes.

Role Context

HugClaim sits at the intersection of AI reliability and insurance outcomes. This data analysis role is central to that loop: identify where failures concentrate, isolate why they happen, and show which interventions materially change outcomes.

• Define and maintain canonical metrics for claims lifecycle, trust, severity, and mitigation impact.
• Partner with engineering to improve event reliability and reduce blind spots in product telemetry.
• Deliver clear recommendations with tradeoffs, confidence levels, and next-step actions.

First 90 Days

• Complete a telemetry audit and publish a metric dictionary used by product, research, and leadership.
• Launch dashboards that segment failures by user type, workflow step, and estimated financial impact.
• Run at least one experiment analysis that directly drives a shipped product or mitigation decision.
• Create a recurring analytics review that tracks movement on top reliability priorities.

Example Projects You Would Lead

Beyond routine reporting, this role is expected to structure ambiguous problems and produce decision-quality analysis that changes roadmap direction.

Claims Funnel Stability

Pinpoint the highest-loss drop-off points in the claim flow and recommend measurable fixes.

Mitigation ROI Modeling

Estimate which model or policy interventions reduce repeat failures at the best cost/performance ratio.

Trust Signal Forecasting

Build early-warning metrics that detect rising user dissatisfaction before support volume spikes.

Cross-Functional Collaboration

• Product managers for claims and chat experiences.
• Backend and data engineers for event design, data quality, and pipeline reliability.
• Model and evaluation teams translating analysis into mitigation priorities.
• Leadership stakeholders making portfolio-level quality and investment decisions.

Success Profile

• Strong statistical judgment and practical experimentation experience in production environments.
• Comfort with incomplete data and ability to communicate uncertainty clearly.
• Track record of influencing product direction with concise and defensible analysis.
• MS/PhD or equivalent experience in statistics, data science, econometrics, OR, or computer science.

Compensation

IC4: USD $119,800 - $234,700 (San Francisco: $158,400 - $258,000)

IC5: USD $139,900 - $274,800 (San Francisco: $188,000 - $304,200)

Application

Submit your application through our standard role form.