Battery Data Scientist

• Development and Implementation of state of the art statistical and machine learning models for cell failure detection

• Development and implementation of early prediction of battery cycle life using Bayesian Optimization and machine learning models

• Lead the analytical direction toward understanding battery performance and degradation

• Research and development of multivariate models for prognostics applications, predictive maintenance

• Support and work with cross functional team to design experimental plans to identify and quantify key model parameters, and improve cell string performance by understanding physical meaning correlated with simulation and experiment

• Design and implement practical workflows for battery technicians to identify batteries in need of maintenance and track and measure impact of maintenance measures before/after.

Battery Lab Operations

• Apply lab-based learnings to field data for prognostic recommendations and problem identification.

• Implement, test, and validate models with field data.

• Report and monitor on-going lab testing.

• Write documentation on algorithm and model improvements to clearly communicate the structure of new methods and implementations, including justification.

• Build software products and algorithms to estimate state of charge (SoC), SoC Imbalance, SoH, Useable Energy, Round trip efficiency, and other battery level performance metrics, including collaboration with product and engineering teams.

• The candidate must be able to embrace the fast and dynamic environment of a growth stage company, comfortable with adjusting quickly to changing priorities.

• 5+ years of experience in data science or a related field with demonstrable/proven result developing and implementing statistical and machine learning models, particularly in areas like predictive maintenance, anomaly detection, and lifecycle prediction.

• Knowledge of lithium-ion battery simulation techniques or electrical power systems engineering or strong motivation to learn

• Strong programming skills in Python, (5+ years) with experience in data analysis libraries (e.g., Pandas, NumPy) and machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).

• Previous experience working with IoT-connected devices, or familiarity with managing and analyzing large volumes of time-series data from IoT sensors.

• Research related to and knowledge of lithium-ion batteries or strong motivation to learn

• Master’s degree (or equivalent experience) in Data Science, Machine Learning, Applied Mathematics, or a related field. A Ph.D. is a plus.

• Proficiency with data visualization tools and techniques for clear communication of findings. Experience with Redash, Grafana, Metabase or Looker is preferred.

• Track record of working cross-functionally, particularly with R&D and engineering teams, to integrate data science solutions into product development.

• Experience in writing technical documentation for models, algorithms, and processes, explaining their structure, assumptions, and justifications.

• Ability to adapt to a fast-paced, evolving environment, with experience handling multiple priorities.

• Experience in a lab environment, with familiarity in applying experimental findings to real-world applications and managing validation processes.

• Experience with Bayesian Optimization and multivariate analysis techniques will be an added advantage.

• Strong desire to learn and adapt

• Flexibility and ambition to work in a fast-paced startup environment

Zembo Electric Motorcycles SMC Ltd offers a fun, supportive work environment and opportunities for continued professional growth within a fast-growing global enterprise. It is an Equal Opportunity  and considers all applicants regardless of race, colour, religion, sex, marital status, sexual orientation, national origin, HIV/Aids, disability, or any other protected characteristic as established by law.