Data Scientist EV(electric or gas utility) - Remote

ideaHelix; United States; Remote; USD 90,000 - 130,000; Full time

Job summary

A leading company in the energy sector seeks a Data Scientist EV to design algorithms for analyzing customer energy consumption and predicting Electric Vehicle adoption. The role requires a Ph.D. and experience with large datasets, offering a dynamic environment to apply data science in the utility industry.

Qualifications

• 2+ years of experience with large-scale time series data.
• Experience developing and maintaining scientific code at scale.
• Knowledge of best practices in model building, evaluation, optimization.

Responsibilities

• Design and develop algorithms in Python for customer energy consumption.
• Perform in-depth validation and root-cause analysis of ML models.
• Collaborate with team members and communicate technical information.

Skills

Data science standards

Spatio-temporal statistics

Geospatial data analysis

Machine learning techniques

Applied statistics

Problem-solving

Communication skills

Education

Ph.D. in Engineering, Computer Science, Physics, Econometrics, Economics, Mathematics, Applied Sciences, Statistics

Tools

Python

R

AWS

Azure

GCP

Job description

Data Scientist EV (electric or gas utility) - Remote

Relevant industry experience (electric or gas utility, EV charging infrastructure, Vehicle-Grid integration, distributed energy resources, analytics consulting, etc.)

What you will do:

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

Basic Qualifications:

1. Ph.D. in Engineering, Computer Science, Physics, Econometrics or Economics, Mathematics, Applied Sciences, Statistics, or other highly quantitative discipline.
2. Knowledge of data science standards and processes (model building, evaluation, optimization, feature engineering) and best practices.
3. Experience with spatio-temporal statistics, geospatial data analysis, and machine learning techniques for large datasets.
4. 2+ years of experience working with large-scale time series data.
5. Proficiency in Python and/or R.
6. Experience developing and maintaining scientific code at scale.
7. Strong understanding of applied statistics and probability.

Desired Qualifications:

1. Experience with large datasets and cloud platforms (AWS, Azure, GCP, etc.).
2. Ability to translate business needs into technical requirements and develop analysis plans.
3. Relevant industry experience (electric or gas utility, EV infrastructure, Vehicle-Grid, distributed energy).
4. Excellent problem-solving and communication skills.

Seniority level

• Mid-Senior level

Employment type

• Contract

Job function

• Information Technology

Industries

• IT Services and IT Consulting