Data Scientist, MTS

Quantum Scape is on a mission to transform energy storage with solid-state lithium-metal battery technology. The company’s next-generation batteries are designed to enable greater energy density, faster charging and enhanced safety to support the transition away from legacy energy sources toward a lower carbon future.

Manufacturing Quality is a diverse group of engineers and data scientists who bring deep expertise in materials science, electrochemistry, statistics, and machine learning. Our team thrives on data-driven decision-making and a shared commitment to drive continuous improvement to Quantum Scape’s solid-state battery technology. We work closely with the Manufacturing, Reliability, and R&D groups to identify failure modes, engineer critical-to-quality specifications, and implement robust control strategies across all process areas.

The Manufacturing Quality team is seeking a mid-level engineer who is proficient with data science methodologies and is excited about improving the quality and reliability of our solid-state Li metal batteries. You will support specification development activities interfacing with multiple cross-functional departments across the company. The ideal candidate has a hard sciences background, statistics and data science experience through coursework or industry, and the ability to communicate complex technical information to a diverse group of stakeholders.

If you enjoy problem-solving and thrive in a highly collaborative, fast-paced environment, we’d like to hear from you.

• Design and implement new specifications based on in-line metrology inspection systems (e.g. optical, 3D, radiograph) across film, cathode, and cell assembly processes to drive improvements to the quality and reliability of our batteries.
• Leverage machine learning or traditional statistics methodologies to identify in-process metrics that are best predictive of electrical performance. Identify strategy to increase cell reliability based on the learnings.
• Develop machine learning models to classify components or features based on underlying knowledge. Coordinate labeling, development, validation, and implementation of models.
• Define and validate statistically-valid sampling strategies to accept/reject batches based on measurements of a small subset of parts.
• Communicate complex technical information to cross-functional stakeholders with refined presentations and weekly write-ups. Propose path forward based on learnings.
• Continuously study state-of-the-art data science methodologies through AI-assisted literature review, critically identify best options, and rapidly apply them to internal projects.

• B.S. & 3+ years of experience or M.S. & 1+ years of experience is required. Educational background preferably in Materials Science, Chemical Engineering, Chemistry, Physics, or equivalent engineering field.
• Strong programming skills with 2+ years of relevant experience through coursework or industry.
• Proficiency with Python data science and machine learning libraries, such as Pandas, Scikit-learn, Sci Py, Tensor Flow, PyTorch, etc.
• Proficiency with SQL to query data from database and data warehouse storage (i.e.: GCP’s Big Query).
• Industry or academic experience with statistical analysis for manufacturing processes, like regression (i.e.: linear, logistics), t-tests, comparison of different test groups, etc.
• Experience developing machine learning models such as tree-based models (i.e.: decision trees, random forest, XGBoost, etc.) or deep learning models (i.e.: neural networks, autoencoders, etc.) to predict binary or continuous outcomes using large, complex datasets.
• Excellent written and verbal communication skills to collaborate closely with cross-functional colleagues.

• 2+ years of experience in the battery manufacturing industry.
• Hands-on experience with battery assembly, failure analysis, or characterization techniques.
• Proficiency with AI coding tools to accelerate data analysis and visualization, model development, etc.
• Proficiency with SQL to query data from database and data warehouse storage.
• Proficiency with JMP, Microsoft Office,…