div>A Bachelor's or Master's degree in advanced mathematics, computer science, machine learning, or statistical methods is required:
With a Master's degree, 7 years' of hands-on experience performing the following is required
With a Bachelor's degree, 9 years' of experience is required:
Manipulating data sets, querying databases, and building statistical models
Statistical or data mining techniques
Using Web Services
Analyzing data from 3rd party users
Developing data models and algorithms
Creating and using advanced machine learning algorithms and statistics
Knowledge and understanding of financial analysis/budgeting, risk analysis, probability and statistics, and electric utility operations
With a Bachelor's degree, at least 10 graduate credits in computer science algorithms, statistics, software design, or data management OR one of the following Data Science Certifications or similar are also required:
Certified Analytics Professional (CAP)
Data Science Council of America (DASCA) Senior Data Scientist (SDS)
Data Science Council of America (DASCA) Principle Data Scientist (PDS)
Dell EMC Data Science Track
Google Certified Professional Data Engineer
Google Advanced Data Analytics Certificate for Machine Learning
IBM Data Science Professional Certificate
Mathematics experience including multivariate calculus, linear algebra, differential equations, and real analysis:
Probability and Statistics: including stochastic processes, classical inference techniques, maximum likelihood estimation, Bayesian methods, Monte Carlo, and bootstrapping.
Computer Science: design and analysis of algorithms and data structures, computational complexity, search methods.
Supervised Learning (e.g., regression techniques, regularization techniques, ridge regression, ensemble methods, optimization through linear programming and convex optimization, nonlinear programming).
Unsupervised Learning (e.g., clustering techniques, hierarchical clustering, dimensionality reduction, principal component analysis).
Time Series Analysis.
Demonstrated knowledge of computer languages including, but not limited to Python, Java, SQL, and R.
Experience with R software product(s).
Energy/utility industry experience.
Experience with Power BI (Microsoft Business Intelligence).
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