Data Science Consultant (Intern/Co-op Conversion) - Johnson

Build an exciting, rewarding career with us - help us make a difference for millions of people every day. Consider joining the Duke Energy team, where you'll find a friendly work environment, opportunities for growth and development, recognition for your work, and competitive pay and benefits.

The data scientist will support the growing analytics needs of the company. This position is responsible for business consulting activities for internal business customers within various Duke Energy business units as the primary interface and as a liaison to Information Technology in order to:

* Serve as an expert in translating complex data into key strategy insights and valuable actions.

* Discover business narratives told by the data and present them to other scientists, business stakeholders, and managers at various levels.

* Develop and test heuristics

* Create, train, test, run and refine models

* Perform data exploration and data mining

* Create business intelligence, dashboards, visualizations, and/or other advanced analytics reports to adequately tell the business narrative and offer recommendations that are practiced, actionable, and have material impact, in addition to being well-supported by analytical models and data.

Basic Qualifications:

• Must have obtained Bachelor's and/or Masters degree in computer science or related field from an ABET accredited program by official start date.
• Only previous Duke Energy interns/co-ops may be considered

• Mastery of statistics, machine learning algorithms and advanced mathematics.
• Strong knowledge of basic and advanced predictive models.
• Knowledge of electricity and natural gas utility business model and operations.
• Basic knowledge of Linux command line interface.
• Basic knowledge of cloud platform tools and techniques.
• Basic knowledge of Hadoop ecosystem, including tools for data mining and analytics, including Sqoop, Hive, Pig, Spark and/or Scala.
• Experience with SAP HANA for predictive analytics.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
• Data mining knowledge that spans a range of disciplines.
• Strong exploratory analysis skills.
• Excellent verbal and written communication skills as well as the ability to bridge the gap between data science and business management.
• Exceptional organizational skills and is detail oriented.
• Capable in using visualization tools to deliver results.

• Hybrid - Work will be performed from both remote and onsite locations after the onboarding period. However, hybrid employees should live within a reasonable commute to the designated Duke Energy facility. Reliable, consistent transportation is required to ensure timely arrival at the applicable facility.

• Working knowledge of statistics and predictive modeling.

• Working knowledge of code writing and programming.

• Understanding of and ability to use programming languages for predictive modeling, like Python, R or SAS.

• Understanding of and ability to use scripts like SQL (Structured Query Language) and / or Hive for accessing and wrangling data.

Travel Requirements

Posting Expiration Date

All job postings expire at 12:01 AM on the posting expiration date.

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