Our Team

Jesse Smith is an applied statistician whose work is centered around estimating the impacts of demand side interventions to alter the way homes and businesses use energy. Over the last decade in the energy industry, Jesse has been involved in the evaluation, measurement and verification (EM&V) of a wide variety of demand response, dynamic pricing, and energy efficiency programs implemented by electric and gas utilities across North America. He specializes in statistical analysis of energy usage data, sampling, experimental design, and benefit cost modeling and is comfortable working in Stata, SAS, SQL, and Excel. He received a BS in Psychology from the University of North Carolina at Chapel Hill and a MS degree in Applied Statistics from Kennesaw State University. Prior to founding Demand Side Analytics in 2016, Jesse worked as a managing consultant at Nexant and as a load research analyst for GoodCents Solutions where he performed statistical analyses of the energy and demand savings of a number of direct load control and energy efficiency programs for client utilities.

Josh Bode specializes in advanced applications of data analytics using large volumes of hourly and sub-hourly data for evaluation, valuation, planning and forecasting in the energy sector. He has led over 50 studies including some of the first innovations and largest applications of smart meter and SCADA data analytics in topics as varied as:

• Impact evaluations of time varying pricing, demand response, behavioral programs, and energy efficiency programs;
• Location specific probabilistic forecasting and planning methods, including locations specific T&D marginal costs;
• DER valuation and cost-effectiveness;
• Market potential studies of DER’s including distribution level micro-potential studies, and
• Value based targeting analytics

As part of these studies he has worked with smart meter data for millions of residential and small and medium businesses and with the full population of large customers from numerous utilities. He also has applied experience with large scale transmission level, substation, and distribution circuit feeder hourly data from multiple utilities, including PG&E, ConEdison, O&R, Central Hudson, NYSEG, RG&E, and National Grid (Rhode Island). Most recently, he has worked on projects designed to align distributed energy resources with grid value and in developing location specific, probabilistic forecasts and T&D marginal costs. He received a BS in Business Economics from Willamette University and a Master’s degree in Public Policy from the University of California, Berkeley.

Ms. Lemarchand’s work has focused an array of Distributed Energy Resources (DERs) from solar photo-voltaic to electric vehicles to demand response all in the context of Non Wires Alternative assessment and sustainable DER rate and program design. This work has included DER valuation, market and empirical research design and analysis to align DER program and rate design with corporate goals, and strategic Utility of the Future road mapping for utilities seeking to incorporate DERs into distribution planning and corporate strategy. Last year, Alana assisted Central Hudson’s development of a Distributed System Implementation Plan (DSIP) including granular load and DER forecasting. Alana also co-authored a paper in which DER valuation approaches were recently laid out, SEPA Beyond the Meter: Addressing the Locational Valuation Challenge for DERs. More recently she has supported design and planning of a DER technology agnostic prices-to-devices pilot.

Prior to shifting her consulting focus to the utility industry, Ms. Lemarchand was a Senior Consultant at Simon-Kucher & Partners, a pricing strategy consultancy, where she managed project teams focused on developing pricing strategies for a diverse array of companies including consumer internet start-ups, providers of small business services, and enterprise software giants, among others. Ms. Lemarchand holds a B.S. in Environmental Economics and Policy from the University of California, Berkeley, where she graduated as the top student in her class and was selected as the commencement speaker.

Ms. Ciccone has extensive expertise with analysis of smart meter data, rate design, potential studies, and impact evaluation for pricing, demand response, and behavioral programs. Some recent examples of her work include:

• Analysis of revenue neutral cost-based rate design for over 2,000 time varying, demand and demand subscription rates including impacts on customer bills and volatility.
• Analyzing energy savings for behavioral programs for Seattle City Light
• Implementing the analysis for the California Statewide Non-residential Critical Peak Pricing and the California Baseline Interruptible Program for multiple years
• Estimating impacts using smart meter and interval data for utility programs at SDG&E and SCE.
• Contributing to the pricing analysis and development of adoption propensity scores for 12 million customers (both residential and non-residential) as part of the California Demand Response Potential Study
• Implementing baseline accuracy studies for the California ISO and Commonwealth Edison. The CAISO baseline accuracy study included testing of accuracy for over 5,000 baseline rules using smart meter and interval data from approximately 500,000 DR program participants for over 10 programs at PG&E, SCE, and SDG&E.

Prior to joining Demand Side Analytics, Adriana Ciccone worked at Nexant and Procter & Gamble.  She attended MIT for college, where she double majored in Operations Research and Materials Science & Engineering.  She also holds a MS degree in Environmental Science and Policy from the University of Chicago. Her graduate studies included program evaluation, computer science, and energy economics and policy.

Ms. Bieler is a Principal Consultant based in Denver, Colorado. She focuses on demand-side management evaluation projects, as well as strategic market assessments and planning studies. Stephanie has led several demand response market potential studies for investor-owned utilities and evaluated several of the largest DR programs in California. She has also studied and quantified the value of resilience and grid modernization investments by estimating customer interruption costs. Stephanie earned her Master’s degree at Stanford University, where she specialized in resource management, geographic information systems (GIS), and advanced statistical analysis.

Mr. Morris is an applied statistician with wide exposure to evaluation with interval data. Since joining Demand Side Analytics, he has contributed to a variety of energy efficiency and demand response evaluation projects and supported the development of the IPMVP Option C uncertainty guidelines for the Efficiency Valuation Organization. He is versed in three of the most prominent statistical packages – R, SAS, and Stata – and has experience translating code from one language to another. He attended the University of Georgia, where he received the Hollingsworth Award for excellence in undergraduate mathematics and received an MS in statistics. He currently teaches statistics at Kennesaw State University.

Examples of recent projects include:

• Analysis of NY vehicle registration data (11.9M vehicles) to develop granular forecasts of electric vehicle adoption, including assessing the impact on hourly (8,760) substation load forecasts. As part of this project, he analyzed the rate of vehicle turnover, estimated the historical penetration over time of electrified vehicles, estimated innovation diffusion curves, estimated adoption propensity scores over time, developed 8760 hourly EV load shapes, and assessed the impact of electric vehicle adoption on substation loads.
• Analysis of peak reduction impacts from smart thermostats. As part of this project, he used 5-minute thermostat run-time data to estimate summer and winter peak load reduction impacts. Helped develop an automated tool that implements the analysis within 24 hours of each event and draft a report that is sent to the client.
• Audit analysis of seven large scale randomized control trials for  home energy reports behavioral interventions in Pennsylvania, designed to encourage energy conservation of electricity. In total, the randomized control trial includes 1.2 million participants and hundreds of thousands of customers in the control groups.

Dr Blundell is an economist with strong technical skills and over a decade of experience in research and analysis supporting utility operations, maintenance, and planning. During his PhD studies, he held a position as a graduate student affiliate with the Energy Institute at Haas. His own research lies at the intersection of energy and transportation; his job market paper examined the location decisions of firms providing electric vehicle fast charging stations. As an experienced utility analyst and consultant, he enjoys employing economic modeling, causal inference, and machine learning methods to address client needs and tackle compelling questions.

Andrea’s primary areas of interest are the integration of distributed energy resources, consumer energy use analysis, and load forecasting. She is experienced with statistical and machine learning computing and visualization languages, including Python, Stata, Excel, Tableau, and Power BI. Examples of recent project work include:

• Automating the collection of EV vehicle registration data to provide up to date information on EV penetration and adoption for each municipality in NY
• Developing a specialized bill calculator with AMI data to analyze customer bill impacts with and without solar, battery storage, and DR
• Developing analytics dashboard for identifying and targeting high-value for DR, battery storage, and solar + battery storage
• Analyzing water heater five-minute data to assess the ability to utilize water heater for battery storage and shift loads in response to time-of-use and demand rates
• Performing and accuracy assessment of meter-based energy savings estimates used for energy efficiency pay-for-performance and on-bill financing programs

Andrea holds a BS in Earth & Environmental Science from the University of Michigan. Before joining DSA she worked for Solar United Neighbors and USGS.

Ms. Horner joined Demand Side Analytics in 2021 after completing a Master’s in Economics at Georgia Tech., where she also served as a graduate research assistant in the School of Public Policy. Her research interests lie in using quantitative methods to assess the effectiveness and economics of different policy interventions. She is experienced in several statistical language statistical programming languages including Stata, Python, and R.

Tim Larsen is an economist who specializes in applied econometrics. He loves policy analysis and is fascinated by energy markets, their structure, regulation, and innovation.  Mr. Larsen has a PhD in Economics from the University of Colorado and taught economics for several years at Colorado, Vanderbilt, and Berry College. His courses ranged from development economics to macroeconomics and his research focused on historical discrimination and corruption.

Hal joined DSA in 2023 after completing his Ph.D. in Agriculture and Resource Economics from UC Berkeley, where his research focused on using large datasets to study energy efficient and climate-friendly consumer products, and where he taught a course on energy markets. Hal has extensive training in causal inference and experimental design and has experience working in economics at both think tanks and in the private sector.

Mr. Farr joined Demand Side Analytics in 2021, based primarily in North Carolina. Previously, he completed a bachelor’s degree in economics from the University of Georgia and a master’s degree in economics from the University of Texas at Austin. He has experience managing Demand Response evaluations in multiple states as well as NMEC analysis. He also has experience modeling future time-varying emissions rates for use in cost-effectiveness tests. His research interests center around using statistical modeling to understand program impacts and ways to improve their effectiveness.

Molly serves as both the administrative cornerstone of the company and the director of the Demand Side Analytics recruiting team. Molly is responsible for human resources tasks, employee benefits organization, sourcing & onboarding new hires, event planning, marketing, and (she contributes to) proposal writing for new business development. Molly leads a team of recruiters who primarily connect with the residential and commercial customers of utility companies and regulatory agencies to enlist their engagement in energy efficiency programs and studies. This outreach also includes hosting stakeholder interviews, promoting survey participation, scheduling site inspections, large-volume email distribution, and administration of program incentive payouts. Molly’s recruiting team holds a 115% recruitment success rate for completed projects.

Molly designs and teaches biweekly Pilates classes as part of the company’s wellness program. In her personal time, Molly can be found with her family in the kitchen or at the lake.

Prior to joining Demand Side Analytics, Michael studied psychology, philosophy, and neuroscience at Washington University in St. Louis and worked in client services and product management at two Chicago-based technology companies. Michael is experienced with data wrangling, visualization, and statistical modeling, including time series forecasting and deep learning, and his top skills include Python, SQL, Tableau, Excel, and Stata. He is passionate about working collaboratively to modernize the grid, and his primary interests include distributed energy resource planning, load forecasting, and smart meter data analytics. When he’s not inside reading or cooking, Michael can be found rock climbing and exploring our nation’s beautiful parks.

John Walkington is an economist whose interests include machine learning, causal inference methods, and applied statistics for the social sciences. John graduated with a Master of Arts in Economics from The University of Texas at Austin in 2022. John’s work at Demand Side Analytics has included the evaluation of several demand response programs for all three California IOU’s, including smart thermostat programs, critical peak pricing programs, and the statewide Emergency Load Reduction Program (ELRP). He has also assisted with long-term gas system planning in New York in accordance with the Climate Leadership and Community Protection Act (CLCPA) goals of decarbonization and building electrification. John has extensive experience utilizing AMI data, utility billing data, end-use data, and geodata in assisting utilities and regulatory agencies to answer key questions in program evaluation and planning.

Patrik Karlovic is an Applied Data Scientist at Demand Side Analytics. With an MS in Data Science from Bellevue University, Patrik combines his knowledge of data with a practical approach to environmental challenges. His work focuses on using data to understand how various programs influence and improve energy grid efficiency. Previously, Patrik applied his skills at a large agricultural producer, using analytics to enhance production workflow and safety in fertilizer manufacturing. Proficient in Python, R, Stata, and various other software, Patrik is passionate about connecting data and energy to build a cleaner, more efficient power grid in an ever-evolving climate. When not working, he enjoys hiking in Oregon’s forests with his dog or immersing himself in Portland’s local music scene.

Candace completed a data science Master’s degree at UC Berkeley while working as a product intelligence intern for an aerospace company, prior to joining Demand Side Analytics in 2023. She has experience with data analysis, machine learning, and optimization methods using Python, SQL, and MATLAB. Since joining DSA she has contributed to various transportation electrification, DER forecasting, and energy efficiency load shape analysis projects.

Sophie Andrews employs skills in data manipulation, econometrics, and data visualization to answer questions related to the ongoing energy transition. She brings over six years of experience in academic economics research at UC Berkeley and Stanford University, including in survey design and regression analysis using Stata, R, Python, and more. In her free time, Sophie is a dedicated athlete who loves climbing and weightlifting.

Parker’s interests lie at the crossroads of data science and energy analysis. After completing his Master’s in Economics at the University of Texas at Austin, Mr. Gauthier has brought to Demand Side Analytics his skills in economic modeling, regression analysis, and machine learning. With DSA, Parker has gained hands-on experience in conducting a variety of analyses on topics such as demand response, time-of-use electricity rates, and regulatory policy. His experience has facilitated his understanding of the electricity grid, underpinning both technical insights and effective communication with a diverse clientele. Parker’s technical skills are founded in programming languages such as STATA, R, SQL, and Python. This combination equips him to provide effective analyses of a wide variety of utility programs.  Examples of recent project work include:

• Automating rapid evaluations for demand response events using hourly AMI data
• Verifying electric and gas savings due to the implementation of energy efficiency measures using relevant Technical Resource Manuals
• Estimating impacts to water usage from landscape transformations using daily usage data
• Performing a review of claimed savings from residential solar installations using hourly AMI data
• Analyzing load shifting and price elasticities as a result of electric vehicle time-of-use rates

Nixon is a Data Scientist with a background in Economics, specializing in causal inference research designs applied to real-world problems. His expertise lies in leveraging predictive modeling techniques, including machine learning algorithms, to drive actionable insights from complex datasets. With a deep understanding of economic principles and advanced statistical methodologies, Nixon combines his skills to deliver comprehensive analyses and inform data-driven decision-making strategies. Passionate about using data to solve challenges, he effectively communicates complex concepts and collaborates with diverse teams and stakeholders. Nixon’s goal is to help organizations optimize their strategies and achieve their goals by harnessing the power of data.

Zhuoning joined Demand Side Analytics in 2023 after completing a Master’s in Economics from Duke University where she worked as a research assistant focusing on policy evaluation. Zhuoning has experience working with statistical programming languages, including Stata, R, and Python as well as visualization software such as Tableau. She is passionate about survey design and analysis, demand response evaluations, and distributed energy resource planning.

Melissa joined the Demand Side Analytics recruiting team to assist in the coordination of recruitment for various energy research studies. Melissa has over 10 years of experience working in recruiting, marketing, database and call center management, and lead generation in the financial sector with both corporate and individual clients. Prior to this role, Melissa served as Project Manager and has extensive consulting and sales support experience. In her free time, Melissa enjoys family activities, sporting events, and the beach.