Duration: 12+ months Contract
- Between 5-8 years of relevant experience developing hypotheses, applying machine learning algorithms, validating results to analyze multi-terabyte datasets and extracting actionable insights is required. Previous research or professional experience applying advanced analytic techniques to large, complex datasets.
- Strong understanding in at least two of the following areas: machine learning, artificial intelligence, statistical modeling, data mining, information retrieval, or data visualization.
- Basic experience in developing and deploying predictive analytics projects using one or more leading languages (Python, R, Scala, etc.).
- Ability to translate data analysis and findings into coherent conclusions and actionable recommendations to business partners, practice leaders, and executives. Strong oral and written communication skills.
- Prior exposure to data structures pertaining to smart-meters, billing, or outage management systems.
- Prior exposure to the utilities or broader energy sector.
- Prior exposure to the full spectrum of data science lifecycle, including data acquisition, maintenance, processing, analysis, and communication.
- Ability to look at things differently, debug, troubleshoot, design and implement solutions to complex technical issues.
- Expert level coding skills (Python, R, Scala, SQL, etc), and experience developing in a Unix environment.
- Exposure working with open source software and Unix OS.
- Bachelor's degree/ Master's degree in a Quantitative discipline.
Ex: Applied Mathematics, Computer Science, Finance, Operations Research, Physics, Statistics, or related field