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, are a quick learner, have a strong sense of ownership, and are excited to learn about wholesale power market operations. As a member of the Modeling and Optimization team at Tyba, you will have the opportunity to contribute to a mission-critical product that synthesizes price forecasts and bid optimization algorithms to deliver strong 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
Train and evaluate forecasting models for new applications and use cases.
Develop features for nodal electricity price forecasts, working with power market experts to identify predictive signals and integrate them into our forecasting infrastructure.
Investigate model behavior in specific contexts, such as diagnosing forecast misses and identifying their root causes.
Benchmark model performance by analyzing price forecast and battery dispatch backtests, defining the metrics that matter, and building dashboards to track them over time.
Communicate model performance and behavior clearly to internal stakeholders and customers.
Required Skills
Master’s degree in CS/Statistics/Finance/Operations Research OR 2 years of experience working in related fields
Passion for working in clean energy and a strong willingness to build knowledge of power market fundamentals
Experience with Python and its package ecosystem (Pandas, PyTorch, plotting libraries), as well as SQL
Experience with time series forecasting, ideally at high frequency and demonstrated by concrete projects
Comfortable with machine learning models and concepts
Comfortable working in Git
Ability to work cross-functionally on an interdisciplinary team
Experience with energy and/or financial 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.
Compensation / Benefits
Salary: $130K - $170K
Benefits: Parental leave, medical benefits, unlimited PTO.
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.
