Senior Data Science Consultant - Power System Economics and Optimization

Duke Energy Corporation-posted 10 months ago
Full-time • Mid Level
Charlotte, NC
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This position is responsible for the development, application, and maintenance of data, models, and software used to support the economic planning and operation of Duke Energy’s $6B multi-commodity fuel & power portfolio and 50 GW+ regulated thermal and renewable generation fleet. Typical applications include evaluating and integrating renewable energy technologies, optimizing energy storage, simulating commodity prices, forecasting fuel requirements, and other related topics. We are looking for a talented individual with strong programming skills to automate data flows, develop mathematical models, generate insights from data, and author compelling technical documents and presentations to help the organization make data-driven business decisions.

  • Develop code to transform and automate data flows from market data providers, internal business units, and external vendors to run large generation fleet optimization models and extract outputs for reports.
  • Take ownership of existing or new models and analytic tasks supporting the optimization of the economics and reliability of Duke Energy assets and systems.
  • Evaluate assumptions, accuracy, and performance of models.
  • Frequently update/maintain models as technical and business requirements change.
  • Present models, analyses and insights to technical and business audiences.
  • Communicate/educate and train at all levels in the organization.
  • Establish and manage tools and practices to optimize performance of large data applications including on-premises and cloud databases.
  • Author technical documents and white papers for internal and external audiences, create compelling visualizations and contribute to regulatory filings and testimony.
  • Follow best practices for model governance and business continuity including version control, robustness/fault tolerance, model documentation, and peer training.
  • Create interactive dashboards and reports to maximize the value of data and forecasts in business decision making throughout the organization.
  • Bachelor’s degree in Engineering, Computer Science, Mathematics or related field.
  • Minimum 5 years related work experience.
  • Strong programming skills in data science/mathematical software packages specifically MATLAB, Python, SAS or R; MATLAB and Python expertise strongly preferred.
  • Strong understanding of probability distributions, stochastic processes, tail risk estimation.
  • Excellent communication and presentation skills with ability to communicate technical subjects to a wide range of audiences.
  • Practical experience with real-world implementation of regression and machine learning models.
  • Experience with mathematical optimization techniques and production cost models.
  • Practical knowledge of timeseries simulation methods and related analysis including PCA, covariance analysis, cointegration, ARIMA and Box-Jenkins analysis.
  • A general understanding or strong interest in utility, power, gas, oil or coal industries.
  • Practical experience managing data in traditional (Oracle, SQL Server) and/or cloud databases (AWS).
  • Able to create tables/views and query large databases with minimal assistance.
  • Practical experience developing dashboards in data visualization tools such as Qlikview and Power BI.
  • Advanced knowledge of Excel and VBA.
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