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:

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

Required Qualifications:

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