Data Scientist II (Hybrid - US) - Energy Solutions - USA : Job Details

We are currently seeking a full-timeData Scientist II to join our Energy Efficiency team to support our market transformation programs, with a focus on building electrification. In this role, you will work closely with a team of data scientists, data engineers, and technical project managers and will collaborate with engineers and program managers.

The Data Scientist II in this role will support the application of mathematical models, statistics, data visualization, and data engineering to answer important questions. Examples of such questions include, “What would be the energy, environmental, economic, and health impacts of this proposed regulation?” “How can we predict which households will be most likely to switch to electric equipment?” “How much more expensive are heat pump clothes dryers when you control for confounding variables?” “What percentage of heat pump sales have gone to households living in Disadvantaged Community census tracts, within a 95% confidence interval?” Modeling will include statistical analysis as well as bottom-up, stock-rollover models rooted in principles of economic and engineering analysis.

As with all consultants at Energy Solutions, the Data Scientist II will work on an evolving portfolio of various projects, including some multi-year initiatives and shorter-term projects. A typical week consists of a mixture of team meetings, working sessions with other team members, asynchronous collaboration, and individual work.

This position is contingent upon Energy Solutions securing the consulting engagement it's tied to. Once the contract is awarded to us, we'll be ready to move forward quickly; however, if it does not come through, we will not be able to proceed with the position. Confirmation of the contract is expected by late September, with the expectation that the selected candidate will start in October.

This is a hybrid work opportunity. At ES, this means working onsite at one of our offices a minimum of 1 day/week (currently Wednesdays) with flexibility for the remainder of the days. ES has offices in Oakland, CA, Portland, OR, Chicago, IL, and Boston, MA. At this time, we are not accepting applications from candidates residing in the following states: Alaska, Delaware, Kentucky, Mississippi, Montana, Nebraska, North Dakota, and Wyoming.

Responsibilities include but are not limited to:

• Develop, maintain, and run robust analytical models and dashboards for internal and external clients
• Build Python-based ETL pipelines in collaboration with other data scientists and project managers
• Apply machine learning and regular expressions for fuzzy string matching and data reconciliation
• Own the quality and accuracy of data analyses, working with data engineers and other team members to develop quality assurance systems and flag data errors
• Communicate and collect information from other staff, subcontractors, and clients
• Translate quantitative findings into clear, actionable insights for non-technical audiences
• Mentor and guide other members of the data analysis/engineering team

Minimum Qualifications:

• Bachelor's degree in a quantitative field (e.g., Statistics, Engineering, Computer Science, Economics) or equivalent experience
• 5+ years of relevant work experience
• 3+ years of hands-on Python experience, including pandas, NumPy, and scikit-learn
• Proven professional experience developing dashboards using BI tools, preferably Tableau
• Experience building analytical models using a high-level programming language
• Knowledgeable about the applicability and limitations of metrics commonly used in descriptive and inferential statistics
• Capable of working independently and collaborating effectively with technical as well as non-technical project managers
• Able to navigate multiple interrelated and simultaneous projects
• Adapt at communicating technical concepts to non-technical audiences
• Strong critical thinking and evidence-based reasoning skills

Please note: A technical test will be required during the interview process

Preferred qualifications:

• Degree in Statistics, Mathematics, Physics, Economics, Operations Research, Engineering, a related quantitative field, or equivalent practical experience
• Proficiency with Tableau
• Knowledge of basic data warehousing principles
• 1+ years of experience with SQL, with demonstrated proficiency
• Experienced in selecting and implementing machine learning techniques where appropriate
• Domain knowledge on topics such as economics, engineering, public policy, the electricity grid, regulations, building codes, building science, incentive programs, demand-side management, energy efficiency, distributed energy resources, electrification, space and water heating, and energy equity
• Enthusiastic about combating climate change and learning about clean energy and policy
• Team player who thrives in collaborative environments
• Humility, empathy, and strong listening skills

Compensation to commensurate with experience with the pay band of $110k - $135k/Annually