EV Data Scientist

Jobs via Dice; California (MO); Remote; USD 103,000 - 156,000; Full time

Job summary

A leading tech company is seeking an EV Data Scientist to develop algorithms and predict adoption trends for electric vehicles. The role requires a Ph.D. in a quantitative field and expertise in programming and machine learning. This remote position is ideal for candidates passionate about energy consumption and electric vehicle technology.

Qualifications

• Ph.D. in a highly quantitative discipline is required.
• Experience in data science processes and spatio-temporal statistics.
• Proficiency in Python or R with a strong understanding of statistics.

Responsibilities

• Design algorithms in Python for customer energy consumption.
• Develop algorithms to predict Electric Vehicle adoption.
• Collaborate with domain experts to understand business requirements.

Skills

Electric Vehicle

Machine Learning

Data Science

Statistical Analysis

Python

R

Education

Ph.D. in Engineering, Computer Science, Physics, Econometrics, or Mathematics

Tools

AWS

Azure

Google Cloud Platform

Job description

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Dice is the leading career destination for tech experts at every stage of their careers. Our client, Enexus Global, is seeking the following. Apply via Dice today!

Title: EV Data Scientist

Location: Remote

Exp: 15+

W2 / C2C

Skills: Electric Vehicle

Job Descripton:

• 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.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  Software Development

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