Staff Scientist

FirstFuel Software is the energy intelligence company that helps utilities engage their commercial customers and rapidly achieve energy efficiency across commercial building portfolios.

FirstFuelCompany: FirstFuel
Location: Lexington, MA

Company Overview
FirstFuel Software is the energy intelligence company that helps Utilities engage their commercial customers and rapidly achieve energy efficiency across commercial building portfolios.

Using patent-pending analytics that disaggregate whole building consumption into end-uses, the FirstFuel RBA platform combining electric interval and gas meter data with high-frequency weather and climate data, as well as GIS mapped building characteristics to produce a consistent, reliable view of how energy is being used inside each building. The remote analysis creates immediate benefits for utilities and their commercial building customers - leveraging the platform to:

  • Benchmark - Buildings at an end-use level against comparable buildings by size, type and region;
  • Recommend - Actionable, customized energy conservation measures by end-use - both operational and retrofit opportunities;
  • Monitor - Building's or entire portfolio's to verify actual end use energy savings, and support disclosure and labeling mandates.

Founded in 2010 and backed by top-tier VCs, FirstFuel is headquartered in Lexington, MA. For more information please visit

Position: Staff Scientist
The Staff Scientist will join a top-flight R&D team with decades of deep academic and industry experience. As part of an industry-leading Venture-backed startup on a rapid growth path, s/he will be expected to juggle multiple responsibilities: s/he will be equally comfortable in developing state of the art statistical and Machine Learning algorithms as well as deploying them using the best practices of software engineering applied to a scalable, secure, cloud-based architecture. S/he must have the ability to switch contexts rapidly between Research literature search, rapid prototyping and testing and deployment. Finally, s/he will be both a self-starter and a consummate team player.

Main responsibilities include: developing the core statistical and machine learning algorithms with the Research group; coding these algorithms in production quality software with the engineering team; work in close collaboration with the engineering and building science teams in running production models and interpreting the results; mine industrial-size data sets in various states of cleanliness to gain insight on underlying patterns; pattern recognition and capture via variable creation and selection; automation and scaling of model building process; deploying and monitoring model performance and initiate continuous model quality improvements; help develop next generation products and solutions.

Work will require effective cooperation with local and global teams. This position is not expected to involve significant (greater than 15%) travel.



  • Advanced degree (MS required, Ph.D. strongly preferred) in a quantitative field e.g., Operations Research, Computer Science, Statistics, Electrical Engineering, Physics, Econometrics, etc.
  • 3+ years developing models in Matlab®.
  • 5+ years of strong programming skills with extensive experience with at least one Object Oriented language like Java. Must have coded extensively and be prepared to demonstrate examples.
  • Must have developed and deployed advanced algorithms and /or statistical models with "real life" data.
  • Deep knowledge of analytic methodologies (linear & nonlinear regression, signal processing, simulation, optimization, neural networks, etc.).
  • Passion for energy and clean technologies.


  • Developed models in one or more Statistical packages like Matlab®, SAS®, SPSS®, R, RATS®, Stata®.
  • Proficiency in one or more of Unix shell scripting, Ruby, Perl, C++, Python.
  • Cloud platform programming experience (e.g., Amazon Web Services).
  • Work experience in a startup or small technology driven company.

To apply for this position, please send your cover email and CV to