Data Scientist

Data Scientist IV Charlotte, NC This position is responsible for data science consulting activities: 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 and run models. Perform data exploration and data mining. Solving predictive and prescriptive problems by applying techniques from mathematics, statistics, computer science and related disciplines. Developing software products and services in collaboration with our engineering, science, and business vertical teams. Basic/Required Qualifications: • Solid background and understanding (Mastery) of advanced mathematics, statistical and machine learning models, and algorithms • 5 + years of experience (Proficient) of programming languages for statistical and ML modeling, Python/R, experience with Spark and big data/cloud platform (AWS, Azure) • Building and delivering enterprise scale software, i.e., ability to generalize models and deliver production level code, including error handling, testing, etc. • Understanding of and ability to use scripts like SQL (Structured Query Language) and / or Hive for accessing and wrangling data. • Excellent verbal and written communication skills as well as the ability to bridge the gap between data science and business management. • Master’s or doctoral degree in business analytics or an advanced computer programming field, statistics, physics, mathematics, engineering, computer science, management of information systems, or related fields or an MBA. Work experience in addition to degree: 5+ years. Desired Qualifications: • Mastery of statistics, machine learning algorithms and advanced mathematics. • Strong knowledge of basic and advanced predictive and prescriptive models • Knowledge of electricity and nuclear 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. • 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