At a glance
- Employment
- Full-time
- Workplace
- Onsite
- Location
- Austin, TX
About the role
- Quant Analysts build and improve the models that drive Base’s Trading & Risk platform - the system that spans our distributed fleet of batteries and the households we serve.
- You’ll own the price models that tell Base where value exists in wholesale markets like ERCOT and PJM, and the hedging strategy that turns that analysis into a plan for managing Base’s risk.
- This is a mid-to-senior role that combines quantitative analysis, software engineering, and energy market expertise.
Responsibilities
- Improve Base’s price distributions by capturing grid congestion effects, like midday price excursions regularly seen, that our current models miss
- Build a price model for PJM, so Base can track risk and make hedging decisions there as well as it already does in ERCOT
- Build a hedging strategy for PJM, using the models you build to decide what that strategy should be
Requirements
- Energy markets and domain knowledge: you understand wholesale energy market operations like ERCOT, including real-time arbitrage, ancillary services, and capacity, along with unit commitment, economic dispatch, and production cost modeling
- Coding and SQL: you build models in Python (or another language) and pull your own data with SQL, and you can work through a model independently
- Statistics and machine learning: You understand the bias-variance tradeoff, train/validation/test evaluation, and loss functions for categorical and continuous targets, and you’re deeply familiar with at least one statistical subfield, like extreme value theory, information theory, or stochastic processes
- You’ve deployed models to production with versioning and maintenance, scaled training beyond a single machine, and know Python, pandas, and visualization libraries well
Skills
- Python
- SQL
- Pandas
