About GridwareGridware is a San Francisco-based technology company dedicated to protecting and enhancing the electrical grid. We pioneered a groundbreaking new class of grid management called active grid response (AGR), focused on monitoring the electrical, physical, and environmental aspects of the grid that affect reliability and safety. Gridware’s advanced Active Grid Response platform uses high-precision sensors to detect potential issues early, enabling proactive maintenance and fault mitigation. This comprehensive approach helps improve safety, reduce outages, and ensure the grid operates efficiently. The company is backed by climate-tech and Silicon Valley investors. For more information, please visit www.Gridware.io.About the Role As an Applied Research Scientist on theData Opportunities team, you will lead the design and development of statistically grounded, scalable pipelines and model prototypes that power our decision systems and dashboards. Your work will span data engineering, statistical analysis, and machine learning experimentation, ensuring data reliability and scientific rigor. This position offers an opportunity to shape future product development at Gridware by leveraging data science to strengthen grid resilience and mitigate wildfire threats.
Responsibilities
- Design and run exploratory analyses to trends, anomalies, and signal
- Build interpretable baseline models and apply hypothesis testing to validate features
- Estimate performance, uncertainty, and feature importance using appropriate statistical methods
- Build and maintain data pipelines to ingest, clean, and transform sensor, time-series, and spatial data
- Engineer robust features using statistical, temporal, and frequency-based techniques
- Package insights into clean datasets, visualizations, and concise summaries
- Collaborate on dashboards and reports that communicate findings clearly and credibly
- Partner with engineers, scientists, and stakeholders to align models with product and operational needs
- Maintain version control and contribute to shared research and data tooling standards
Required Skills
- Bachelor’s or Master’s in Data Science, Statistics, Engineering, or related
- 1–3 years’ experience in a data-science or data-engineering role
- Proficient in Python (pandas, scikit-learn), SQL
- Basic geospatial skills: familiarity with geopandas,xarray,rasterio, or Google Earth Engine
- Comfortable running and interpreting machine learning models
- Strong analytical mindset and debugging skills
- Familiarity with version control and code review workflows (Git/GitHub)
Bonus Skills
- Prior work with weather or environmental remote-sensing data
- Experience with ETL automation
This describes the ideal candidate; many of us have picked up this expertise along the way. Even if you meet only part of this list, we encourage you to apply!BenefitsHealth, Dental & Vision (Gold and Platinum with some providers plans fully covered) Paid parental leave Alternating day off (every other Monday)“Off the Grid”, a two week per year paid break for all employees. Commuter allowance Company-paid training
