Designs, develops, and executes scripts, programs, models, algorithms, and processes using structured and unstructured data.
Participates in internal and external communities of practice in data science/artificial intelligence/machine learning.
Educates the non-technical community on advantages, risks, and maturity levels of data science solutions.
Researches and applies advanced knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions.
Solves unique and complex strategic issues and problems while developing and monitoring budgets, forecast models, dashboards, presentations, and ad hoc analysis.
Creates advanced data mining architectures / models / protocols, statistical reporting, and data analysis methodologies.
Extracts, transforms, and loads data from dissimilar sources.
Applies data science/machine learning/artificial intelligence methods to develop defensible and reproducible predictive models.
Wrangles and prepares data as input of machine learning model development and feature engineering.
Writes and documents reusable python functions and modular python code for data science.
Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, and analytic procedures.

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.
Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience.
Active participation in the external data science/artificial intelligence/machine learning community of practice.
Competency with data science standards and processes (model evaluation, optimization, feature engineering, etc.)
Knowledge of industry trends and current issues in job-related area of responsibility.
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.

Data Scientist – Expert

Key skills