Senior Data Scientist

Recurve Analytics

Recurve is hiring a Senior Data Scientist to help build the next generation of the FLEX Platform. We work at national scale with one of the largest energy datasets available: AMI interval data for more than 50 million electricity and gas meters, combined with weather, geospatial context, distribution-grid attributes, and more. If you want serious machine learning challenges grounded in real operational needs, this is that environment.

Our mission is to unlock the power of demand-side energy resources and make them visible, trusted, impactful, and accessible to all. Your work will contribute directly to grid affordability, reliability, and sustainability.

The role

You will lead data science activities that combine statistical modeling, machine learning, and AI techniques to support more effective deployment and use of demand-side energy resources. The work spans measurement, forecasting, disaggregation, segmentation, and the development of more predictive and proactive capabilities.

You will improve existing models while developing new ones, applying AI and machine learning techniques where they create meaningful value. Your models and code will become part of the FLEX Platform and be used in production by utilities, regulators, and market participants.

This is an applied data science role. You will build production-ready analytics for the FLEX Platform while partnering with customer-facing teams to apply those capabilities to real-world utility challenges. The strongest candidates enjoy both building software and working directly with domain experts to translate customer needs into reusable platform capabilities.

What you will do

• Working under limited supervision, lead the development and refinement of statistical and ML models for load, flexibility, and customer behavior
• Analyze AMI, customer, and grid data to identify patterns for system planning and program design models
• Apply sound judgment to select the appropriate statistical, machine learning, or deep learning approach for each problem.
• Review methods and collaborate with other data scientists to improve analytical approaches
• Collaborate with domain experts to ensure models reflect real grid behavior, program design, and customer characteristics
• Validate models with structured backtesting, cross-validation, and uncertainty analysis
• Communicate assumptions, limitations, and tradeoffs clearly to cross-functional partners
• Develop efficient and maintainable code and models
• Produce clear, reproducible documentation 
• Partner with customer-facing teams to support customer engagements and develop new analytical approaches that can be incorporated into the FLEX Platform
• Translate customer requirements and field experience into reusable platform capabilities

What we’re looking for

• Experience applying data science to energy systems, demand response, energy efficiency, distributed energy resources, utility operations, or other complex problems in the energy industry
• Strong subject-matter knowledge in power systems, demand-side management, or related area
• Senior-level ability to lead analytic work with moderate to high complexity (equivalent to 5-8 years of relevant experience post Bachelor’s degree; advanced degree preferred)
• Expertise in a variety of modern supervised and unsupervised machine learning techniques
• Strong Python and SQL skills with experience developing clean, production-ready code
• Depth in Python data science tools like pandas, NumPy, SciPy, scikit-learn
• Experience with time-series and panel data analysis
• Strong data visualization skills
• Experience supporting customer-facing analytical projects or translating customer requirements into production software
• Solid grounding in statistics, uncertainty, and causal reasoning
• Ability to collaborate effectively with data science and engineering colleagues and influence cross-functional partners
• Ability to communicate technical concepts effectively with both technical and non-technical stakeholders
• Demonstrated ability to balance analytical rigor with practical engineering tradeoffs

Nice to have

• Hands-on neural-network modeling using frameworks like PyTorch or TensorFlow
• Experience with sequence modeling or deep learning for time series
• Experience with geospatial modeling and analysis
• Experience with DER device-level data
• Experience with agentic code development workflows
• Interest in ML approaches adaptable to distributed or device-adjacent inference
• Advanced degree in engineering, physics, mathematics, or related technical discipline

Why Recurve

Recurve is dedicated to solving planetary challenges by decarbonizing the grid. Our analytics directly support the transition to a reliable, affordable, and sustainable energy future.

Utilities and regulators rely on Recurve to understand load growth, electrification impacts, and where the grid is under pressure today. Our analytics help determine which customers drive system peaks, what actions reduce load, and how programs and investments should respond. The work is visible, consequential, and directly tied to grid reliability and customer affordability.

Recurve offers production-scale data, deep technical challenges, and a collaborative team of data scientists and domain experts. If you want to apply advanced ML and analytical judgment to real grid challenges at national scale, we’d like to talk.