Data Scientist
Tyba · United States
- Hybrid
- Full-time
- $170,000 / year
- United States
Job highlights
- Develop battery auto-bidding platform models.
- Analyze and forecast electricity prices.
- Improve predictive models for energy infrastructure.
- Work with Python, SQL, and ML.
- Contribute to clean energy transition.
About the role
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
Key skills/competency
- Data Science
- Machine Learning
- Time Series Forecasting
- Python
- SQL
- Energy Markets
- Optimization
- Data Analysis
- Model Development
- Forecasting Models
Skills & topics
- Data Scientist
- Python
- SQL
- Machine Learning
- Time Series Forecasting
- Energy Markets
- Clean Energy
- Data Analysis
- Model Development
- Forecasting
How to get hired
- Research Tyba's mission: Understand their focus on renewable energy and their modeling platform.
- Tailor your resume: Highlight your Python, SQL, machine learning, and time series forecasting skills.
- Showcase clean energy passion: Emphasize any experience or interest in the clean energy sector.
- Prepare for technical and behavioral questions: Be ready to discuss past projects and problem-solving approaches.
- Apply early and follow instructions: Submit a complete application and tailor your cover letter if applicable.
Technical preparation
Behavioral questions
Frequently asked questions
- What is the interview process for a Data Scientist at Tyba?
- Tyba's interview process for a Data Scientist focuses on core competencies and mutual fit. It typically involves initial conversations about Tyba and your background, followed by evaluations of your relevant skills and experience. The process prioritizes transparency and clear communication to ensure a good match for both the candidate and the company.
- What are the salary expectations for a Data Scientist at Tyba?
- The compensation range for a Data Scientist at Tyba is between $130,000 and $170,000 annually. This range reflects the experience and responsibilities associated with the role.
- Does Tyba offer remote work options for Data Scientist roles?
- Yes, Tyba offers a flexible work environment that includes remote work options, alongside a hybrid work model. This allows for flexibility in how and where Data Scientists perform their duties.
- What benefits does Tyba provide for its employees, including Data Scientists?
- Tyba offers a comprehensive benefits package including parental leave, medical benefits, and unlimited paid time off (PTO). Additionally, employees have the opportunity to receive equity options, granting them a stake in the company.
- What specific technical skills are most important for a Data Scientist at Tyba?
- Key technical skills for a Data Scientist at Tyba include proficiency in Python (with libraries like Pandas and PyTorch), SQL, machine learning concepts, and time series forecasting. Experience with Git and understanding of energy or financial data is also highly valued.
- How does Tyba support professional development for its Data Scientists?
- Tyba encourages continuous learning and growth. As a Data Scientist, you'll have the opportunity to deepen your knowledge of wholesale power market operations and work on mission-critical products, contributing to significant impact in the clean energy sector.
- What is the desired educational background for a Data Scientist at Tyba?
- Tyba seeks candidates with a Master's degree in Computer Science, Statistics, Finance, or Operations Research. Alternatively, candidates with at least two years of relevant work experience in related fields are also encouraged to apply.