About Tyba
Tyba is a modeling platform for energy companies developing, financing, and operating renewable energy infrastructure. Energy companies rely on technical models daily to make crucial infrastructure decisions. Our mission is to make cutting-edge models accessible to cross-functional teams such that companies can build and operate more renewable energy more profitably.
We apply data science, AI/ML prediction, optimization, and physical modeling to a range of applications that support decision-making, from early-stage siting of power plants to the daily operations of energy storage and solar projects. Our customers access these models via an easy-to-use web application or programmatically through our API and rely on the accuracy of our models and the performance of our software.
The Role
We are looking for a data scientist to join our team to work on modeling initiatives that deliver value to customers of our battery auto-bidding platform.
You will excel in this role if you’re passionate about clean energy, have a strong sense of ownership, and are excited to learn about wholesale power market operations. As a member of the Modeling and Optimization division of Tyba’s Engineering team, you will have the opportunity to contribute to a mission-critical product that synthesizes price forecasts and bid optimization algorithms to deliver market-beating returns for our customers. You will work on a cross-functional team, going deep on the intricacies of power markets to help improve our predictive models. This role primarily involves working on Tyba’s price forecast engine, with a focus on hypothesis-driven model experimentation.
Responsibilities
- Feature development: Work with power market experts on the team to identify predictive features for nodal electricity prices, and integrate them into our forecasting infrastructure.
- Model benchmarking: Analyze results from price forecast and battery dispatch algorithm backtests, identifying important performance metrics and building dashboards and interactive visualizations to track them.
- Performance improvement: Improve the computational performance of the machine learning algorithm and data pipelines.
Desired Skills
- Passion for working in clean energy and a strong willingness to build knowledge of power market fundamentals.
- Experience in time series forecasting and/or probabilistic model calibration, ideally demonstrated by concrete projects.
- Experience with Python and its package ecosystem (Pandas, PyTorch, plotting libraries), as well as SQL
- Comfortable working in Git
- Ability to work cross-functionally on an interdisciplinary team
- Experience with energy data, optimization and data infrastructure is a plus
- Experience with working on ML systems in production is a plus
We understand that everyone’s experience is unique, so if you’re excited about this role, and eager to make an impact on the clean energy transition, but don’t meet every requirement, we encourage you to apply anyway.
Tyba’s Product
Tyba has two main products for customers – Operations and Project Simulation
Operations: Auto-bidding platform, powered by a proprietary neural network, that recommends and executes operating strategies based on industry-leading price forecasts and optimization methodology.
Project Simulation: Configurable simulation platform where developers can model realistic financial and physical outcomes based on location, market dynamics, and battery specifications.
As a data scientist, you’ll primarily work on improving the predictive models used in the auto-bidding platform. There are plenty of opportunities for collaboration on other portions of the operations product, such as optimization and market orchestration as well.
Tyba’s Technical Stack
Tyba’s machine learning stack is developed in Python and runs on the AWS cloud. We rely on PyTorch for building our neural network architectures.
Compensation and benefits:
- Salary: $150k-$220k
- Benefits: Parental leave, medical benefits, unlimited PTO, and a bakery below our HQ.
- Equity Options: Opportunity to own a stake in the company through an employee stock option plan.
- Flexible Work Environment: Hybrid work model, remote work options, and team offsites.
FAQ
What is the interview process like?
Our interview process focuses on core competencies. We want to make sure that you are set up for success at a fast-growing and high-impact startup. We will first get to know each other through conversations about Tyba, your background, and what you are looking for in your next role. While the specifics vary, from there, we will focus on evaluating your skills and experience relevant to the role. Once we have determined whether or not you are a fit for the team, we will help you get to know the company better and speak with other team members to inform your decision. We prioritize transparency, clear communication, and ensuring that we do our best to find a mutual fit.
Are you open to remote work?
This role will be based in Tyba’s Oakland office, but we will also consider remote and hybrid working locations for excellent candidates.
