Join our team as an Associate Quantitative Analyst, where you’ll dive into the exciting world of clean energy! In this role, you’ll clean, analyze, and model large panel data sets to evaluate the effectiveness of clean energy interventions and enhance our forecasting and planning efforts. You’ll leverage econometric, statistical, and predictive analytic techniques to conduct in-depth analyses of utility customer energy consumption, energy demand, and customer segmentation. You’ll also work with diverse data streams, including interval energy consumption, utility bills, and telemetry data, to uncover insights that drive impactful decisions. If you have a passion for data and advancing the adoption of clean energy solutions, this is the opportunity for you.
- Clean and analyze large datasets using R
- Apply appropriate analytical and statistical techniques to answer research questions
- Exhibit critical thinking and curiosity including considering how your analysis fits within the “big picture” for the project and client
- Produce high-quality analytical outputs (e.g., visualizations, tables) and contribute to client reporting
- Participate in quality control processes
- Develop and apply effective practices to minimize errors in your own work
- Participate in peer code review
- Maintain awareness of priorities and deadlines in coordination with manager
- Bachelor’s degree with 0-3 years of experience (depending on relevance)
- Required degree: Economics, statistics, data science, quantitative social science, or other quantitative field
- Coursework in econometrics, statistics, machine learning, or predictive analytics
- Programming skills in R or Stata
- Passionate about clean energy and wants to advance adoption of clean energy solutions through creative and rigorous application of data analytics
- Exceptional attention to detail
- Highly motivated, with a demonstrated track –record of thinking critically about your work
- Strong written and oral communication skills
- Ability to juggle and prioritize multiple tasks and deadlines simultaneously and flexibly
- Strong preference for intermediate or better R programming skills
- Experience with the tidyverse package suite or data.table
- Experience with version control software (e.g. Git) and collaborative code development
- Experience with Databricks or Spark
- Programming skills in Python
- Coursework in or applied experience with:
- The energy industry, including energy efficiency, demand response, and/or distributed energy resources programs and initiatives
- Utility sector economic analysis including program and policy evaluation, program cost-effectiveness, load forecasting, and/or valuation of distributed energy resources
- Experience with preparation and analysis of utility load data
Salary range: $75,000 – $105,000 depending on experience.
This is a hybrid role with a mix of weekly in-office and remote work out of one of our offices. Strong preference for our Waltham, MA or Portland, OR locations. Also open to La Jolla, CA.
Please note: Depending on experience, we are open to hiring someone at the Associate Quantitative Analyst (entry level) or Quantitative Analyst (advanced degree and/or some relevant work experience) level.