Senior Data Scientist - Customer Energy Consumption in Utility Domain

Positon: Senior Data Scientist - Customer Energy Consumption in Utility Domain

Location: 100% Remote

Department Overview

The Data Science & Artificial Intelligence Department consists of a "Delivery" team that develop data science and machine learning solutions.

As a Delivery team, this Department uses industry leading data science and change management practices to drive client's transition to the sustainable grid of the future. The Department works cross-functionally across the company to enable data driven decisions applying analytics, as well as improvements to relevant business processes. Deployed to some of client's highest priority arenas, the Department does not specialize in a traditional utility domain, such as asset management or program administration, but instead specializes in extracting useful insights from disparate datasets and facilitating actions informed by these insights.

Position Summary

client is looking for a Data Scientist with experience in delivering data science products end-to-end. In this role, the successful candidates will be uniquely positioned at the forefront of utility industry analytics, having the opportunity to advance client's triple bottom line of People, Planet, and Prosperity.

What you will do:

• Design and develop production-quality scientific algorithms in Python to extract patterns of customer energy consumption, as well as other customers' characteristics and attributes.
• Develop spatio-temporal algorithms to predict adoption of Electric Vehicles by customers.
• Perform in-depth validation of our algorithms that is driven by business and technical requirements.
• Perform deep root-cause analysis, EDA, and error analysis of the ML models.
• Collaborate with members of your team and with domain experts (e.g., Power Distribution, Grid Planning, Clean Energy Transportation) to understand practical implications of your model, to collect business requirements and to deliver results to business partners.
• Communicate technical information, their implications and applications to peers, various business partners, and strategic leaders across the company.

Basic Qualifications:

• Ph.D. in Engineering, Computer Science, Physics, Econometrics or Economics, Mathematics, Applied Sciences, Statistics, or other highly quantitative discipline.
• Demonstrated knowledge of and abilities with data science standards and processes (model building and evaluation, optimization, feature engineering, etc.) along with best practices to implement them.
• Experience with spatio-temporal statistics, geospatial data analysis, and machine learning techniques for time series with large datasets.
• 2+ years of experience writing software to extract features from time series data or large-scale datasets.
• Proficiency in programming languages such as Python and/or R.
• Experience designing, developing, and maintaining scientific code that runs at scale.
• Strong understanding of applied statistics and probability.

Desired Qualification:

• Experience with handling large datasets and cloud computing platforms (e.g. AWS, Azure, Google Cloud Platform, or other enterprise level analytics platforms.
• Experience turning business needs into technical requirements, and structuring developments, analysis and validation plans to meet requirements.
• Relevant industry experience (electric or gas utility, EV charging infrastructure, Vehicle-Grid integration, distributed energy resources, analytics consulting, etc).
• Excellent problem solving and communication skills.