Title:  Data Scientist, MTS

QuantumScape 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.

About the team: 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 QuantumScape’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.

What we need: 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.

What You’ll do:

• 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.

Skills You’ll Need:

• 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, SciPy, TensorFlow, PyTorch, etc.
• Proficiency with SQL to query data from database and data warehouse storage (i.e.: GCP’s BigQuery)
• 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.

Nice to have:

• 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, VSCode, and Github Copilot.

Physical requirements:

• Work is performed in an office.
• Sitting or standing for extended periods of time.

HYBRID: This position is required to work onsite at least 4 days per week to meet the minimum essential duties and requirements of this position.  As a data scientist in the Manufacturing Quality team, in-person face-to-face interaction is essential to building authentic relationships, trust, teamwork, and collaboration. 

Compensation & Benefits: The expected salary range for this role is from $134,400 to $174,700, and a final salary will be determined by the candidate's experience and educational background. QuantumScape also offers an annual bonus and a generous RSU/Equity package as part of its compensation plan. In addition, we do offer a tremendous benefits plan including employee paid health care, Employee Stock Purchase Plan (ESPP), and other benefits. 

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive benefits and privileges of employment. Please contact us to request an accommodation.