At Stable, you’ll build the foundation of EV charging businesses worldwide. Our software is already used by some of the biggest EV charging operators and developers in the U.S. to deploy billions of dollars in EV infrastructure, and we’re just getting started.
You’ll work alongside a cast of software engineers, machine learning specialists, data scientists, and problem solvers to transform complex consumer behavior, energy pricing, and incentives into actionable insights that propel charging businesses toward greater scale and sustainability.
We believe that the widespread adoption of electric vehicles is crucial for a greener and more sustainable future, and by facilitating the growth and success of the EV charging ecosystem, we can propel the world towards a sustainable transportation revolution.
Our flexible working culture allows everyone to set their own schedule and location to best suit their working style around a core window of overlapping hours. That means that we’re primarily remote, but we also offer co-working access and intentionally create in-person moments to foster collaboration and connection.
We also have great healthcare plans, 401k, parental leave, and a host of other benefits. You can see the full list here: Stable Benefits
We are looking for a data scientist to help us build and scale our breakthrough EV infrastructure intelligence platform.
You will help us navigate the complex challenges of building and managing the tools needed to help charging companies deploy and operate millions of EV chargers across the world. The clock is ticking on climate change, and with hundreds of thousands of EV chargers needed in the next few years, Stable's platform will be essential to deploying them smarter and faster.
You are a data scientist but you will have the opportunity to tackle large and varied problems outside of your role as we scale our business.
- Work closely with Stable’s data science team to build powerful machine learning models to predict & improve EV charging station performance.
- Build simulations to forecast future trends and understand operational dynamics at EV charging stations.
- Design and run experiments to optimize charging station operations and revenue.
- Design and implement data pipelines for model development and performance monitoring.
- Explore dynamic datasets and craft analyses and visualizations to elegantly communicate complex interactions in simple terms.
- Understand customer needs and identify opportunities for innovation.
- Build and apply models to guide product direction with evidence and data.
- Lead the charge. Some decisions are truly marginal, and we trust you to make the best decisions you can. Expect autonomy and full support when you need it.
- You want to join a fast-paced, early-stage startup, working to clear a path for all-electric transportation.
- You are curious and excited to tackle hard problems.
- You are able to communicate complex ideas simply.
- You can quickly iterate, navigate uncertainty, and identify when things are not working.
- You are a kind, humble, generous collaborator.
- Bachelors or Masters in Computer Science, Mathematics, Engineering, or a related field.
- At least 2 years of work experience in machine learning or data science, or 4 years if no Masters degree.
- Experience contributing to production software code.
- Experience processing and visualizing geospatial data, designing and running causal inference experiments, building predictive models, and/or building simulations.
- Familiarity with Python, data science libraries, RESTful APIs, and cloud infrastructure (GCS, AWS).
- Bonus: You have prior experience in transportation, urban systems, electrical grids, or other related domains that take care of large spatial datasets and/or deal with the interaction between the built environment and real-time market pricing.
Stable is an equal-opportunity employer. Whatever it is that makes you, well, you--whether it be race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or anything else—we’d love to hear from you. And we welcome applicants based anywhere in the U.S.