Data Scientist, Expert

Role Overview

Designs, develops, and executes scripts, programs, models, algorithms, and processes using structured and unstructured data from disparate sources and sizes, generating defensible, valid, scalable, reproducible, and documented machine learning and artificial intelligence models for problem solving and strategy development.

What You Will Do

Researches and applies advanced knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions. Creates advanced data mining architectures/models/protocols, statistical reporting, and data analysis methodologies to identify trends in structured and unstructured data sets.

Why It Might Be a Fit

Participates in internal and external communities of practice in data science/artificial intelligence/machine learning to advance knowledge in the field. Educates the non-technical community on advantages, risks, and maturity levels of data science solutions.

Requirements

• Bachelor’s Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
• 6 years in data science (or no experience, if possess Doctoral Degree or higher, as described above).
• Competency with data science standards and processes (model evaluation, optimization, feature engineering, etc) along with best practices to implement them.
• Knowledge of industry trends and current issues in job-related area of responsibility as demonstrated through peer reviewed journal publications, conference presentations, open source contributions or similar activities.
• Competency with commonly used data science and/or operations research programming languages, packages, and tools for building data science/machine learning models and algorithms.
• Proficiency in explaining in breadth and depth technical concepts including but not limited to statistical inference, machine learning algorithms, software engineering, model deployment pipelines.
• Mastery in clearly communicating complex technical details and insights to colleagues and stakeholders.
• Mastery of the mathematical and statistical fields that underpin data science.
• Ability to develop, coach, teach and/or mentor others to meet both their career goals and the organization goals.
• Previous experience working with utility data.
• Previous experience with load forecasting, working with utility customer data, consumption patterns, and outage data.
• Working knowledge power flow concepts and tools such as PLSF, PSS-E, TARA, PROMOD, PLEXOS.
• Previous experience with cloud-based infrastructure services across compute, storage, network, and operating system layers along with an understanding of cloud architecture.

Benefits

• Dental insurance
• Vision insurance
• Medical insurance
• 401(k) plan
• Paid time off
• Paid holidays