Senior Battery Data Scientist

5 days ago


Billerica, Massachusetts, United States Factorial Energy Full time

We are seeking a highly skilled Senior Battery Data Scientist to join our team at Factorial Energy in Billerica, MA. This individual will lead the development and implementation of advanced statistical and machine learning models for cell failure detection and early prediction of battery cycle life.

Company Overview

Factorial Energy is a venture-backed company dedicated to creating a sustainable future through innovative solid-state battery technology. With a strong portfolio of innovations, including FEST (Factorial Electrolyte System Technology), we have established partnerships with leading automotive companies such as Mercedes-Benz, Stellantis, and Hyundai Motor Company.

Job Description

This role will be responsible for:

  • Developing and implementing state-of-the-art statistical and machine learning models for cell failure detection
  • Early prediction of battery cycle life using Bayesian Optimization and machine learning models
  • Leading the analytical direction toward understanding battery performance and degradation
  • Research and development of multivariate models for prognostics applications and predictive maintenance

Requirements include a MS or PhD degree in Computer Science, Electrical Engineering, Chemical Engineering, Applied Math, or related area, along with 2+ years of experience in implementing statistical/machine learning methods.

Salary and Benefits

The estimated salary for this position is $120,000 per year, with additional benefits including medical, dental, and vision insurance, paid time off, 401(k) plan with employer matching funds, education assistance plan, and short-term and long-term disability coverage.

Skills and Qualifications

Candidates should possess strong knowledge in data-driven predictive model development with application in energy storage systems and experience with HPC/cloud computing, AI/ML codes and techniques, and languages such as Python/C/C++.



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