QuantumScape · 22 hours ago
Data Scientist, MTS
QuantumScape is on a mission to transform energy storage with solid-state lithium-metal battery technology. The Manufacturing Quality team is seeking a mid-level engineer proficient in data science methodologies to improve the quality and reliability of their solid-state Li metal batteries.
AutomotiveBatteryElectric VehicleEnergyEnergy StorageRenewable Energy
Responsibilities
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
Qualification
Required
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
Preferred
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
Benefits
Annual bonus
Generous RSU/Equity package
Employee paid health care
Employee Stock Purchase Plan (ESPP)
Other benefits
Company
QuantumScape
QuantumScape develops solid-state lithium-metal batteries for electric vehicles and other energy storage applications.
H1B Sponsorship
QuantumScape has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2021 (2)
2020 (9)
Funding
Current Stage
Public CompanyTotal Funding
$1.55BKey Investors
Qatar Investment AuthorityVolkswagen GroupBreakthrough Energy Ventures
2023-08-02Post Ipo Equity· $300M
2021-08-02Post Ipo Equity· $446M
2020-11-27Post Ipo Equity· $500M
Recent News
The Motley Fool
2025-12-21
Benzinga.com
2025-12-17
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