Job Description

Data Scientist

We are looking for a skilled Data Scientist to develop advanced battery health algorithms powered by real-time vehicle data using state-of-the-art statistical and machine learning techniques.

Key Responsibilities:

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  Develop data analysis pipelines to interpret vehicle telemetry and battery usage patterns across various vehicle applications.
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  Design, build, validate, and maintain predictive models that deliver battery health insights for connected battery solutions.
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  Analyze machine and production-line data to better understand manufacturing processes and operational performance.
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  Develop and maintain ML/statistical models aimed at:
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    improving production throughput,
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    reducing scrap rates,
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    enhancing product quality,
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    and optimizing manufacturing efficiency.
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  Collaborate closely with data scientists, engineers, and business stakeholders to design effective, data-driven solutions.
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  Communicate analytical findings and decision-making processes to both technical and non-technical audiences.
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  Support cross-functional teams across the organization with machine learning and statistical modeling expertise.

Required Qualifications:

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  Bachelor's degree in Statistics, Mathematics, Computer Science, Engineering, or a related technical field.
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  3+ years of professional experience in data science, machine learning, or applied statistics, or equivalent academic research experience through a Master's or PhD program.
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  Strong programming skills in Python, Julia, or R, including experience with ML/statistical libraries such as:
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    Scikit-learn,
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    SciPy,
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    Statsmodels,
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    PyTorch,
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    and Keras.
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  Experience using BI and visualization tools such as Power BI or Tableau.
• Strong knowledge of machine learning methods including:
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    supervised and unsupervised learning,
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    feature selection,
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    dimensionality reduction,
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    regression,
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    classification,
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    clustering,
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    and time-series analysis.
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  Experience working with databases and writing SQL queries.
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  Hands-on experience developing, training, validating, and deploying ML/statistical models.