The successful candidate will be proficient in the modeling, estimation and identification of stochastic systems, and will be skilled in the art of stochastic time series analysis. The practice of methods drawn from these disciplines would preferably have been focused on physical processes, likely in the context of design of control systems which operate in an uncertain measurement environment. Qualified candidates may be found in any organization that designs control systems of complex processes. Alternatively, candidates experienced in the analysis and predication of financial time series likely possess many of the requisite skills. Some categorical examples of the subject methods are recited below.
The ideal candidate is a smart mathematically inclined engineer or scientist who will interface with the Chief Scientist, Product Development, Product Management, Sales and key constituents within the organization as well as with customer organizations to help develop new algorithms and solutions which can be deployed within Utilidata systems deployed at the customer distribution grid.
- 7+ years of experience
- Advanced expertise in Matlab
- Modern Control Theory – Knowledge of state space representation and its application in modelling system behavior and feedback
- State Space Representation – Proficient applying a time-domain approach to modelling and analyzing systems with a multitude of inputs and outputs
- System Identification – Experience with System Identification as a discipline in the broader field of control theory, primarily concerned with the formulation and estimation of mathematical representations of processes based on behavioral records, in turn almost always uniformly sampled time series
- (Stochastic) Subspace Identification – Proficient analyzing data signatures and extracting dynamic properties of the system from the collected monitoring data
- Blind Identification – Experience with signal processing in order to understand behavior of multi-dimensional systems from outputs
- Source Separation – Experience with digital signal processing, recovering, original component signals from a combined signal
- Deep knowledge of applied mathematics and statistical analysis, especially as it relates to the electric power grid
- Must possess experience in data management, and the analysis of complex datasets
- Ability to develop models and algorithms, and generate results in a timely manner
- Ability to quickly get up to speed with a range of projects to meet the needs of the business
- Ability to summarize and synthesize inferences
- Ability to work with teams comprising of engineers, software developers, technical sales and marketing to drive the measurement process and satisfy customer requirements
- Data analysis skills using various packages such as SAS, R, and Excel.
- Excellent presentation, written and verbal communication skills.
Minimum of a BSEE with related experience. Master’s Degree in Applied Mathematics, Electrical Engineering or similar field with relevant coursework in applied statistics or information theory preferred.