Senior Research Scientist (Renewable Energy Forecasting)
Job Type: Permanent
Job reference: :
Job Reference: nyc-mw-snr-research
Location: USA, New York, Albany
Sector: Technology, Insight & Data, Renewables
Date Posted: 13/10/2016
Seeking a senior research scientist in the company's Grid Solutions business unit.
The successful candidate will have a deep knowledge of advanced statistical prediction (e.g., machine learning) methods as applied to renewable energy forecasting, as well as experience with systems integration and operations within a successful commercial forecasting business. Candidates should have strong communication (spoken and written) and interpersonal skills, and the ability to work independently and as part of a team. Ability to work effectively with colleagues, meet deadlines, perform high-quality analyses data, assess and validate results, and work on several projects simultaneously is a must. Further, candidates will be able to write, modify, execute, and maintain software in support of internal renewable energy forecasting research initiatives and externally sponsored client projects, have experience meeting deadlines and budgets, perform critical analyses of sensitive data, and ensure timely delivery of project reports and data.
Among other roles, this position will: (a) lead and participate in internal research on topics relating to renewable energy forecasting services; (b) conceive and lead the implementation of initiatives in new business areas; (c) plan, design, and manage major client-sponsored research projects; and (d) represent the company at conferences, client meetings, and other occasions. Prospective candidates will be expected to have a strong professional record in these areas. The position will report to the Vice President of Grid Solutions.
Education: Ph.D. in the physical sciences, mathematics, or computer science is strongly preferred.
Experience: Minimum 5 years of renewable energy or other power industry sector experience preferred. Demonstrated track record managing and leading the design and implementation of prediction systems and the development of software related to machine learning in renewable energy forecasting applications. Familiarity with Linux, FORTRAN, Pearl, Python or similar packages, statistical model software, data analysis and visualization software and methods is preferred. Familiarity with Numerical Weather Prediction models is desirable but not essential.
Spencer Ogden is acting as an Employment Agency in relation to this vacancy.