Remote - United States, USA
1 day ago
Lead Data Scientist Statistician – AV Safety Data Analysis (GPSSC)
Job Description

Work Arrangement

Remote: This role is categorized as remote. This means the successful candidate may be based anywhere in the United States and is not expected to report to a GM worksite unless directed by their manager.

Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.

The Role 

The Lead Data Science Statistician – AV Safety Data Analysis will drive the statistical methods used to development and evaluation of autonomous vehicle (AV) performance safety metrics ranging from straightforward to advanced machine learning outputs.  This position is part of the Safety Assurance for Effective Autonomous Driving Software (SAFE-ADS) department in the Global Product Safety, System, and Certification (GPSSC) organization.  The SAFE-ADS department serves as the central body for automated driving system (ADS) safety. GM’s vision is zero crashes, zero emissions, and zero congestion – AV safety is at the heart of driving forward this vision.  If you seek to solve complex data science challenges and see your work drive positive safety change, this role is for you.   

The ideal candidate will be an expert in data science, statistical modeling, and data development across the entire data maturity curve. They will have experience in automative, safety, and/or robotic industries and understand how to integrate physics and engineering into the foundational statistical methods and approaches. The technical leader is a self-starter and comfortable solving ambiguous problems.  They are passionate about data and creating valuable insights that drive continuous safety improvements and confidence in the system. 

As a technical leader in the SAFE-ADS data science team, you will provide robust statistical expertise and guidance, weigh alternatives, and explain the different approaches to senior leaders.  You will address safety assurance related questions related to ADS behavioral performance and validation.  This role involves working with large-scale data generated by the ADS system. One of the key elements is to scale data science work and accelerating time-to-delivery in insights which requires the integration of physics and engineering principles. As a leader, you'll play a key role in defining and advancing GM's AV quantitative measurement and risk assessment efforts. Your work will contribute to enhancing and scaling our existing safety risk assessment framework and help to ensure coverage of our operational design domain, foundational components of the overall safety case that guides decision-making and drives engineering across the entire AV technology stack. 

What You’ll Do (Responsibilities)

Develop and standardize best practices of statistical estimations and uncertainty model for use in ADS safety risk assessment framework 

Work with the team to develop and implement scalable ADS performance measurement solutions to help ensure safe and compliant on-road behavior and build confidence in the results 

Use an iterative method of development to share early results, identify emerging risks, and provide ongoing guidance 

Assess bias estimation and subsampling strategies used by system engineering 

Support Data Engineering and Software & Services (S&S) in the develop and automate pipelines and tooling of the measurement and risk framework 

Conduct statistical analysis to evaluate ADS driving software aggregate measures 

Raise the bar for on-road safety by continuously improving safety and AV measurement, and developing a feedback loop for software improvements  

Collaborate across various AV development teams, including GPSSC, S&S, Data Engineering, and Legal organizations  

Stay up to date on industry trends and advancements in data science and AI/ML to drive innovation within the team and cross-functionally  

This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate



Additional Job Description

Your Skills & Abilities (Required Qualifications) 

M.S. degree in quantitative discipline (statistics, operations, biostatistics, econometrics, or other relevant degree.)  

8+ minimum years of overall relevant experience, 5 years of which should be experience as a Data Scientist and/or Statistician in a corporate or government setting

Expertise in statistical modeling, machine learning and/or deep learning techniques 

Prior experience with causal inference using instrumented variables and other forms of multifactor attribution methods 

Expertise generating insights from multiple large-scale datasets  

Proficiency in SQL and Python 

Experience with data visualization tools and techniques 

Collaborative team player and excellent communication and interpersonal skills, with ability to engage effectively with technical and non-technical stakeholders 

Strong business consulting skills; ability to evaluate the big picture and solve strategic business problems 

What Will Give You a Competitive Edge (Preferred Qualifications)

PhD in a quantitative discipline (statistics, operations, biostatistics, econometrics, or other relevant degree.)  

Experience in safety, automotive, or robotics data science is preferred 

Compensation:

The expected base compensation for this role is $160,200- $245,400 USD Annually

Actual base compensation within the identified range will vary based on factors relevant to the position

Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance

Benefits:

GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.



About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.



Why Join Us 

We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.



Benefits Overview

From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards Resources.



Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. 

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.



Accommodations

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