Staff Data Scientist - Fleet Analytics and Modeling

Job Description

As a Staff Data Scientist for Fleet Analytics and Modeling, you will generate timely, actionable insights for our B2B customers through retrospective analysis of fleet telemetry data. In addition, you will contribute to our real-time operations and control platform that empowers our customers to maximize productivity and minimize the cost of operating their fleets. You will assist in defining requirements for the ongoing development of our data science and machine learning pipeline framework.

Responsibilities:

1. Use data processing pipeline systems to implement workflows that enable rapid and flexible insight generation and model development at scale.
2. Work with hardware, software, and analytics teams to characterize existing fleets in terms of vehicle performance, business strategy, human behavior, and other dimensions.
3. Generate visually stunning, highly intelligible, information-dense data visualizations for internal and external consumption.
4. Present results of analyses to technical team members, product team, senior management, and other stakeholders.
5. Develop robust models of fleet behavior for use in simulation, prediction, and optimization using statistical learning methods.
6. Assist in the evaluation of novel algorithmic approaches to optimize fleet logistics including advanced energy management and grid-integration of flexible loads.
7. Work with the Product team to define and innovate the deployment of more efficient, on-demand, electrified goods delivery systems.
8. Engage with cross-functional teams to find opportunities to create unique, data-driven products that drive long-term engagement with our software.

Required:

1. Master’s degree or equivalent experience in computer science, data science, engineering, or related quantitative field.
2. 5+ years of industry experience developing and deploying data-driven insights in transportation mobility systems, gaming, scientific simulation, product R&D, or related field.
3. Track record developing innovative solutions to solve complex logistical problems at scale.
4. Deep experience with Python, Jupyter, Pandas, SciKit Learn, and associated tools for statistical and machine learning.
5. Experience working in teams using agile software development methodologies together with distributed version control systems (e.g., git).

Preferred:

1. Experience using big data analytics and workflow orchestration tools at scale (e.g. Databricks, DBT, UbiOps, Luigi, Airflow, Spark, etc.).
2. Experience with A/B testing of data-driven, customer-facing products.
3. Experience integrating simulation systems with distributed, data-intensive processing or analytics applications.
4. Domain knowledge in transportation and energy systems, graph algorithms, convex optimization, and/or reinforcement learning.
5. Familiarity with SQL.

Desired:

1. Experience designing backend data pipelines (framework selection, DAG design, etc.).
2. Self-driven with a passion for transportation decarbonization.
3. Adherence to clean code principles.

This role is categorized as Hybrid. This means the successful candidate is expected to report onsite three times per week at minimum (Tues-Thurs).

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.

Equal Employment Opportunity Statements
GM is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. GM is committed to providing a work environment free from unlawful discrimination and advancing equal employment opportunities for all qualified individuals.