# Bayesian Statistician – Risk & Safety Analysis

Hiring organization: [Torc Robotics](https://career.thegoodapps.co/organizations/torc-robotics)

Canonical page: https://career.thegoodapps.co/jobs/de6e5ea0-91a2-42b1-a24e-24866a9fbf30

Listed on Torc Robotics's own careers site. Applications go to them directly.

- Employment type: full time
- Seniority: Senior
- Location: Blacksburg, VA
- Remote: yes
- Salary: 145900 – 175100 USD per year

## Summary

This role applies Bayesian and frequentist statistics to evaluate safety and risk in autonomous truck systems, translating complex analyses into actionable insights for engineering and leadership teams. It suits statisticians with deep expertise in applied Bayesian methods and experience in safety-critical domains who want to directly influence autonomous vehicle safety decisions.

_Our summary, not Torc Robotics's wording._

## Skills named

Bayesian Statistics, Python, R, SQL, Time Series Analysis

## Required

- Bachelor's degree in Statistics, Computer Science, Robotics, Engineering, or related field plus 6+ years experience, or Master's degree in related field plus 3+ years experience
- Strong background in applied statistics, safety analysis, and risk estimation
- Demonstrated experience applying Bayesian analyses
- Understanding of both Bayesian and frequentist frameworks with ability to select appropriate approach
- Ability to assess whether Bayesian credible intervals have adequate frequentist coverage properties
- Experience in autonomous vehicles, safety-critical domains, or comparable actuarial work
- Experience with complex, real-world datasets
- Hands-on Python experience for analysis
- Clear communication of statistical concepts to non-technical audiences
- Ability to operate independently as technical leader in cross-functional environment
- Domain knowledge in Bayesian methods

## Nice to have

- Experience applying Bayesian methods to estimate risk from disparate data sources
- Knowledge of conservative Bayesian inference principles for safety-critical decisions
- Experience with causal inference methods or Bayesian networks
- Advanced MCMC knowledge and variational inference techniques
- Background in statistics applied to engineering or physics systems
- Familiarity with time-series analysis, uncertainty quantification, or rare-event modeling
- Experience supporting executive decision-making with quick turnarounds

Apply on Torc Robotics's site: https://job-boards.greenhouse.io/torcrobotics/jobs/8600782002