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.