(Sr.) Data Scientist/Engineer/Economist in Advanced Analytics is responsible for providing qualitative and quantitative analytical capabilities to assure the reliable, economic, and coordinated operation of the PJM Interconnection in accordance with PJM Operating Principles and Standards and applicable Regional and NERC Operating Policies.
Because of COVID-19 this position will be temporarily working from home until a return to campus plan is finalized. It is anticipated that most, if not all employees, will return to campus by early 2021. Upon returning to campus, this position is expected to operate on-site.
- The primary focus of the work in the Advanced Analytics department:
- Perform PJM special studies to determine the impact of current/future business rules, industry trends, etc.
- Develop key performance indicators to trend market, operations and planning business performance/challenges
- Analyze big data sets to answer research questions through analytical techniques such as Machine Learning
- Produce PJM’s response to IMM’s State of the Market recommendations
- Collaborate with internal and external business partners to work on challenging problems
- The support functions of this position:
- Support analytics: statistics, operational research, machine learning, econometric modeling, etc.
- Support PJM Market Design process and evolution: data-driven, simulation based, etc. design and evolution
- Support operational research problems: optimization, mathematical modeling, etc.
- Support applicable PJM stakeholder process discussions
- Support writing PJM papers, develop material for PJM board and internal forums
Characteristics and Qualifications:
- BS degree in Economics, Mathematics, Engineering, Data Science
- Experience in analyzing bid data sets.
- Ability to produce high-quality work products with attention to detail
- Ability to visualize and solve complex problems
- Experience using verbal and written communications skills
- Ability to work in a team environment as a team member or as team leader
- MS degree in Engineering, Mathematics, Economics, Data Science or PhD in Engineering, Economics, Mathematics, Data Science
- At least 5 years of experience Energy industry; knowledge in PJM functions would be ideal
- Experienced in using statistical tools such as SAS, Machine Learning algorithms, production cost tools such as PLEXOS, PROBE, formulating optimization problems and publishing papers