Data Scientist

The Data Scientist for our Palo Verde Nuclear Plant is responsible for providing new insights from predictive statistical modeling activities, advanced data analyses, and specialized analytical support for business operations. The Data Scientist will work directly with large amounts of structured and unstructured data from different sources to create meaningful analyses, discover insights and identify opportunities for various business units within the organization. He or she should recommend creative and leading approaches Trend analyses, What-if analyses, Prescriptive and Predictive Data Modeling and provide thought provoking ideas, methods and algorithms to support business decision making. By applying advanced analytics, this role will build mathematical models like Machine Learning, AI, Regression Analysis, supervised and unsupervised modeling techniques to validate findings using experimental and iterative approach.

Works closely with, subject matter experts, project and program managers, architects, data engineers, partners and vendors to turn data into critical information and insights to make sound business decisions. He or she will be able to work effectively independently as well as in a team environment with focus on collaboration and customer satisfaction. The Data Scientist should have creative thinking, strong analytical skills, innovative and curious mindset and excellent organizational and communication skills.

Minimum Requirements

BS degree in Data Science, Computer Science, Information Sciences, Mathematics, Engineering or related fields and minimum 4 years related business experience in analytics, data science, predictive modeling, machine learning, statistical modeling and/or user experience role OR advanced degree and 2 years directly related experience.

Possesses a combination of strong analytical and problem-solving skills and programming knowledge, or an equivalent combination of education and experience with demonstrated comparable knowledge and abilities.

Strong understanding of data analytics methods and tools like R Programming, Python and SQL. Expertise in extracting and transforming large datasets.

Proficient at integrating and preparing large, varied datasets, architecting specialized database and computing environments/platforms, and communicating results. Excellent written and communications skills.

Preferred Special Skills, Knowledge or Qualifications:

Masters or Doctorate degrees in related fields.

Knowledge/experience in utility industry and business functions.

Certification in machine learning and deep learning and/or predictive analytics

Knowledge of Linux, Docker and Kubernetes

Knowledge/Experience in Natural Language Processing

Familiar with TensorFlow

Nuclear requirement: Any PVNGS employee may be called upon to serve as a member of the Emergency Response Organization (ERO) and will be expected to fulfill their obligation as an ERO member. Any PVNGS employee may be called upon to support a refueling or short-notice outage. This includes line roles and responsibilities as necessary to execute outage activities. These are a condition of employment at PVNGS.

Major Accountabilities

1) Collaboration with customers and partners:

Consult with stakeholders and subject matter experts to understand business needs and operations, goals and objectives and key drivers for performance.

Work closely with the business units to complete data analytics efforts. Build and maintain strong working relationships with customers, partners and vendors.

2) Data requirements and preparation:

Identify available and relevant data and the data sources.

Collaborate with SMEs, data stewards and architects for data collection, preparation, integration, quality, exploration and retention.

Gather/Process data and establish performance checks on the large data models.

Design and implementation of solutions including data acquisition, storage, transformation, and analysis

3) Modeling and Deployment:

Design, develop and deploy innovative models. Provide insights from predictive statistical modeling activities. Test theories by creating models and experimenting with data.

Design models, algorithms and visualizations that help distill insights from huge volumes of chaotic data.

Modeling complex problems, discovering insights and identifying opportunities through the use of statistical, algorithmic, mining and visualization techniques using existing or new front-end reporting & analytics tools.

Play key role in turning data into critical information and knowledge that can be used to make sound organizational decisions.

Propose innovative ways to look at problems by using data mining approaches and validate findings using experimental and iterative approaches.

Understand data transforming platforms and technologies and maintain a knowledge of discipline maturity.

4) Present results, provide recommendations and lead analytics efforts:

Present findings to the business in a way that can be easily understood by business counterparts.

Make recommendations based on business requirements and knowledge of industry best practices.

Make technical decisions on advanced analytics initiatives.

5) Programming and Coding

Utilize programming language, such as R, Python, SQL, .net, Java or C++ to evoke the data from data source and model

Familiarity with Cloud structure and building, utilizing cloud technologies

Performing data acquisition using JSon, SQL, ODBC, JScript, or API for Big Data extracts

Transform and utilize streaming data with programming languages such as: KAFKA, SQL, Spark, and/or Azure

6) Mentoring and coaching junior staff as necessary

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