Energy Forecasting Data Scientist: ML & Optimization

Tyba; San Francisco (CA); Hybrid; USD 90,000 - 120,000; Full time

Benefits offered by this job

Parental leave

Medical benefits

Unlimited PTO

Employee stock option plan

Team offsites

Job summary

Tyba is seeking a data scientist dedicated to optimizing their battery auto-bidding platform. This role involves training forecasting models, developing features for price forecasts, and communicating results to stakeholders. Candidates need a Master’s in a relevant field or equivalent experience, along with skills in Python and time series forecasting.

The position offers benefits including parental leave, medical coverage, and the opportunity to participate in the employee stock option plan. Enjoy a flexible hybrid work model while contributing to the clean energy transition.

Qualifications

• Master's degree in a relevant field or 2 years of experience.
• Passionate about clean energy and willing to learn power market fundamentals.
• Experience with Python and its package ecosystem is essential.

Responsibilities

• Train and evaluate forecasting models for new applications.
• Develop features for nodal electricity price forecasts.
• Investigate model behavior and diagnose forecast misses.
• Benchmark model performance and build dashboards.
• Communicate model performance to stakeholders.

Skills

Python

SQL

Time Series Forecasting

Machine Learning

Data Visualization

Interdisciplinary Collaboration

Education

Master's degree in CS/Statistics/Finance/Operations Research

2 years of experience in related fields

Tools

Pandas

PyTorch

Job description

Tyba is seeking a data scientist dedicated to optimizing their battery auto-bidding platform. This role involves training forecasting models, developing features for price forecasts, and communicating results to stakeholders. Candidates need a Master’s in a relevant field or equivalent experience, along with skills in Python and time series forecasting.

The position offers benefits including parental leave, medical coverage, and the opportunity to participate in the employee stock option plan. Enjoy a flexible hybrid work model while contributing to the clean energy transition.