Analytics Research PHD Summer Intern - Chief Data & Analytics Office
About GM
There’s never been a more exciting time to work for General Motors.
To achieve our vision of a world with Zero Crashes, Zero Emissions and Zero Congestion, we need people to join us who are passionate about creating safer, better and more sustainable ways for people to get around. This bold vision won’t happen overnight, but just as we transformed how the world moved in the last century, we are committed to transforming how we move today and in the future.
Why Work for Us
Our culture is focused on building inclusive teams, where differences and unique perspectives are embraced so you can contribute to your fullest potential as you pursue your career. Our locations feature a variety of work environments, including open work spaces and virtual connection platforms to inspire productivity and flexible collaboration. And we are proud to support our employees volunteer interests, and make it a priority to join together in efforts that give back to our communities.
Job Description
This is a remote position, the selected candidate can reside and
perform the work from anywhere within the United States.
Summer/Spring 2021 PHD Internship
The researchers of the Analytics Research team at General Motors Chief Data & Analytics Office help solve the most challenging problems related to GM’s ambitious goal of building a safer, better, and more sustainable world with zero crashes, zero emissions, and zero congestion. Our focus areas include customer insight analytics, marketing analytics, revenue management, quality, safety, future mobility, customer care and aftersales, supply chain, etc. Our team employs talents with diverse background in Operations Research, Management Science, Applied Statistics, Econometrics, Applied Mathematics, Product Development, Supply Chain, Manufacturing, and Engineering.
We are looking for highly motivated students with excellent skills in modeling, analysis, simulation, and optimization of complex, dynamic, stochastic systems. You will collaborate and exchange ideas with top scientists in the fields; and work on cutting edge research that pushes the state of the art and have an opportunity to test your findings on complex real-world problems.
Additional Job Description
Required:
- Current PhD students in a quantitative field including: Operations Research, Management Science, Transportation Research, Statistics, Mathematics, Economics, Data Science, Computer Science, or equivalent.
- Familiar with probability theory, mathematical models, and optimization and simulation methods.
- Good programming skills and familiar with modeling languages such as Python, R.
- Excellent team player and communicator with strong interpersonal skills.
- Excellent oral, presentation and written communication skills.
- Quickly learns and adapts skills to work on projects in and with different technical areas.
- Self-starter and able to work independently on projects with minimal guidance.
- Great work ethic.
Preferred:
- Former experience with big data cleaning and processing, and familiar with SQL query language.
- Familiar with Simio and/or AnyLogic simulation software.
This is a remote position, the selected candidate can reside and
perform the work from anywhere within the United States.
The median level of the monthly salary compensation for this role is $4500 dependent upon class status and degree. Benefit options are not available for this role.
Diversity Information
General Motors is committed to being a workplace that is not only free of discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that workforce diversity creates an environment in which our employees can thrive and develop better products for our customers. We understand and embrace the variety through which people gain experiences whether through professional, personal, educational, or volunteer opportunities.
We encourage interested candidates to review the key responsibilities and qualifications and apply for any positions that match your skills and capabilities.