Data Science Consultant

More than a career - a chance to make a difference in people's lives.

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.

Responsibilities

Partner with Business Clients, establish professional relationship, and communicate with analytics clients in order to understand business needs; Frame Problems with Stakeholder, research and construct problem frames in order to understand the analysis context and scope that will provide timely, useful results. Work in Project Teams and participate in multidisciplinary analytics project teams; Interview Subject Matter Experts, plan and conduct individual interviews with experts to gain valid information and data needed for analysis; Elicit Information from Groups, plan and conduct group elicitation sessions with working groups to develop and assess alternatives, uncertainties, and value and risk preferences. Communicate Results to Decision Makers, explain the Results and conclusions of the analytics process in both written and oral presentation formats.; Create recommendations that are practical, actionable, and have material impact, in addition to being well-supported by analytical models and data. "Employees in this role will also Identify unique opportunities to collect new data. Design new processes and build large, complex data sets. Strategize new uses for data and its interaction with data design. Locate new data sources, analyze statistics and implement quality procedures. Perform data studies of new and diverse data sources. Find new uses for existing data sources. Conduct statistical modeling and experiment design. Develop, test, validate and refine predictive models to optimize customer experiences, revenue generation, operational effectiveness, marketing success and other business outcomes. Build web prototypes and performs data visualization. Conduct scalable data research on and off the cloud. Implement automated processes for efficiently producing scale models. Design, modify and build new data processes. Generate algorithms and create computer models. Collaborate with database engineers and other scientists. Implement new or enhanced software designed to access and handle data more efficiently. Train the data services center team on new or updated procedures. Assist with code review and quality assurance activities. Document and archive models and scripts to enable ongoing support."

Required/Basic Qualifications

• Bachelors degree in Computer Science, Engineering, Mathematics, Statistics, Physics, Management Information Systems, Finance or Economics

• 3 years related work experience

Desired Qualifications

• Masters degree in Mathematics or Statistics

Additional Preferred Qualifications

• 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.

Specific Requirements

• 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.

Working Conditions

• Hybrid Mobility Classification – Work will be performed from both remote and onsite locations after the onboarding period. However, hybrid employees should live within a reasonable daily commute to a Duke Energy facility.

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Travel Requirements

Relocation Assistance Provided (as applicable)

Represented/Union Position

Visa Sponsored Position

Posting Expiration Date

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

Please note that in order to be considered for this position, you must possess all of the basic/required qualifications.

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