<div> Recurve is hiring a Senior Data Scientist to strengthen the analytical core of our 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. We value clear thinking, disciplined methods, and collaboration.The roleYou will lead data science activities that blend established modeling with new ML approaches to support more effective deployment and use of demand-side resources. The work spans measurement, forecasting, disaggregation, segmentation, and the development of more predictive and proactive capabilities.You will improve what exists and build what is missing, keeping up to date on new advancements in data science and applying your learnings in your work. Your models and code will be used in production by utilities, regulators, and market actors.This is an applied data science role within a collaborative team. You will work closely with other data scientists, engineers, and subject-matter experts across Recurve. We expect active engagement, shared problem-solving, and clear communication across the group.What you will do<ul><li style="list-style-type:disc;">Working under limited supervision, lead the development and refinement of statistical and ML models for load, flexibility, and customer behavior</li><li style="list-style-type:disc;">Analyze AMI, customer, and grid data to identify patterns for system planning and program design models</li><li style="list-style-type:disc;">Apply your judgement to select appropriate ML and neural-network frameworks to produce innovative scalable solutions to challenging problems</li><li style="list-style-type:disc;">Work closely with other data scientists to review methods, align approaches, and build shared understanding</li><li style="list-style-type:disc;">Collaborate with domain experts to ensure models reflect real grid behavior, program design, and customer characteristics</li><li style="list-style-type:disc;">Validate models with structured backtesting, cross-validation, and uncertainty analysis</li><li style="list-style-type:disc;">Communicate assumptions, limitations, and tradeoffs clearly to cross-functional partners</li><li style="list-style-type:disc;">Develop efficient and maintainable code and models</li><li style="list-style-type:disc;">Produce clear, reproducible documentation so developments are trusted and understood</li></ul>What we’re looking for<ul><li style="list-style-type:disc;">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)</li><li style="list-style-type:disc;">Expertise in a variety of modern supervised and unsupervised machine learning techniques </li><li style="list-style-type:disc;">Domain experience within energy systems, building science, DERs, or similar complex physical-system data</li><li style="list-style-type:disc;">Strong Python and SQL skills and coding habits that support the production of clean, production-ready code</li><li style="list-style-type:disc;">Depth in Python data science tools like pandas, NumPy, SciPy, scikit-learn</li><li style="list-style-type:disc;">Experience with time-series and panel data analysis</li><li style="list-style-type:disc;">Strong proficiency in building complex yet informative data visualizations</li><li style="list-style-type:disc;">Solid grounding in statistics, uncertainty, and causal reasoning</li><li style="list-style-type:disc;">Ability to collaborate effectively with data science and engineering colleagues and influence cross-functional partners</li><li style="list-style-type:disc;">A desire to build the next generation of innovative solutions to the energy system’s most challenging problems</li></ul>Nice to have<ul><li style="list-style-type:disc;">Hands-on neural-network modeling using frameworks like PyTorch or TensorFlow</li><li style="list-style-type:disc;">Experience with sequence modeling or deep learning for time series</li><li style="list-style-type:disc;">Experience with geospatial modeling and analysis</li><li style="list-style-type:disc;">Experience with DER device-level data</li><li style="list-style-type:disc;">Interest in ML approaches adaptable to distributed or device-adjacent inference</li><li style="list-style-type:disc;">Advanced degree in engineering, physics, mathematics, or related technical discipline</li></ul>Why RecurveRecurve 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 scale, technical depth, and a team of experienced data scientists and domain experts who take a collaborative approach to solving complex problems. If you want to apply advanced ML and analytical judgment to real grid challenges at national scale, we’d like to talk. This is a full-time remote position for a candidate based in the United States.   </div>

Recurve&rsquo;s mission is to accelerate the transition to a clean energy economy by integrating behind the meter demand flexibility resources into the emerging carbon-free energy grid.

Senior Data Scientist

<div> Recurve is hiring a Senior Data Scientist to strengthen the analytical core of our 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. We value clear thinking, disciplined methods, and collaboration.The roleYou will lead data science activities that blend established modeling with new ML approaches to support more effective deployment and use of demand-side resources. The work spans measurement, forecasting, disaggregation, segmentation, and the development of more predictive and proactive capabilities.You will improve what exists and build what is missing, keeping up to date on new advancements in data science and applying your learnings in your work. Your models and code will be used in production by utilities, regulators, and market actors.This is an applied data science role within a collaborative team. You will work closely with other data scientists, engineers, and subject-matter experts across Recurve. We expect active engagement, shared problem-solving, and clear communication across the group.What you will do<ul><li>Working under limited supervision, lead the development and refinement of statistical and ML models for load, flexibility, and customer behavior</li><li>Analyze AMI, customer, and grid data to identify patterns for system planning and program design models</li><li>Apply your judgement to select appropriate ML and neural-network frameworks to produce innovative scalable solutions to challenging problems</li><li>Work closely with other data scientists to review methods, align approaches, and build shared understanding</li><li>Collaborate with domain experts to ensure models reflect real grid behavior, program design, and customer characteristics</li><li>Validate models with structured backtesting, cross-validation, and uncertainty analysis</li><li>Communicate assumptions, limitations, and tradeoffs clearly to cross-functional partners</li><li>Develop efficient and maintainable code and models</li><li>Produce clear, reproducible documentation so developments are trusted and understood</li></ul>What we’re looking for<ul><li>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)</li><li>Expertise in a variety of modern supervised and unsupervised machine learning techniques&nbsp;</li><li>Domain experience within energy systems, building science, DERs, or similar complex physical-system data</li><li>Strong Python and SQL skills and coding habits that support the production of clean, production-ready code</li><li>Depth in Python data science tools like pandas, NumPy, SciPy, scikit-learn</li><li>Experience with time-series and panel data analysis</li><li>Strong proficiency in building complex yet informative data visualizations</li><li>Solid grounding in statistics, uncertainty, and causal reasoning</li><li>Ability to collaborate effectively with data science and engineering colleagues and influence cross-functional partners</li><li>A desire to build the next generation of innovative solutions to the energy system’s most challenging problems</li></ul>Nice to have<ul><li>Hands-on neural-network modeling using frameworks like PyTorch or TensorFlow</li><li>Experience with sequence modeling or deep learning for time series</li><li>Experience with geospatial modeling and analysis</li><li>Experience with DER device-level data</li><li>Interest in ML approaches adaptable to distributed or device-adjacent inference</li><li>Advanced degree in engineering, physics, mathematics, or related technical discipline</li></ul>Why RecurveRecurve 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 scale, technical depth, and a team of experienced data scientists and domain experts who take a collaborative approach to solving complex problems. If you want to apply advanced ML and analytical judgment to real grid challenges at national scale, we’d like to talk. This is a full-time remote position for a candidate based in the United States. &nbsp; </div>

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