Applied Data Scientist: Signal Modeling for Materials

VoltForce; Oakland (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

VoltForce is seeking a Data Scientist to join the Applications Engineering team in a forward-deployed role. You will build and deploy ML models that convert high-dimensional sensor signals into actionable predictions about material properties.

Collaboration with software and hardware teams will move models from research to production. You will work directly with customer samples, validate model performance on novel materials, and translate findings into product improvements and roadmaps.

Qualifications

• Hands-on ML/data science experience with predictive modeling.
• Ability to analyze multivariate, high-dimensional datasets.
• Strong communication of technical findings to varied audiences.

Responsibilities

• Model Development & Calibration: Build, calibrate, and validate predictive models mapping sensor signals to material properties.
• Model Validation & Production Readiness: Develop frameworks for testing, uncertainty quantification, and deployment readiness.
• Customer-Facing PoC: Analyze customer datasets and translate findings into roadmaps for model improvements.

Skills

Python

Machine Learning

Data analysis

Communication

Model validation

Education

B.S. in Data Science, Statistics, Applied Mathematics

M.S. in related quantitative field

Ph.D. a plus

Tools

PostgreSQL

Job description

VoltForce is seeking a Data Scientist to join the Applications Engineering team in a forward-deployed role. You will build and deploy ML models that convert high-dimensional sensor signals into actionable predictions about material properties.

Collaboration with software and hardware teams will move models from research to production. You will work directly with customer samples, validate model performance on novel materials, and translate findings into product improvements and roadmaps.