Data Scientist

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:

• Bachelors 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 Masters 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.