Data Scientist: Signal Modeling for Smart Materials

Activate; San Leandro (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

SirenOpt is seeking a Data Scientist to join the Applications Engineering team. The role focuses on turning high-dimensional sensor data into actionable material-property predictions, bridging research with production deployment.

You will work forward-deployed with customers, validate models on new materials, and collaborate with software and hardware teams to move models into production.

Qualifications

• 3–5 years of applied ML/data science experience (MS 1–3 years; PhD is a plus)
• Hands-on experience building/validating predictive models in Python
• Ability to analyze high-dimensional datasets and perform feature engineering
• Solid grasp of uncertainty quantification and regularization in modeling
• Strong communication skills, able to present findings to diverse audiences

Responsibilities

• Build, calibrate, and validate predictive models mapping sensor features to material properties
• Develop validation frameworks including uncertainty quantification and out-of-distribution detection
• Prepare models and docs for handoff to software engineering for production
• Analyze customer data and translate findings into model improvement roadmaps

Skills

ML/Data science

Python

Feature engineering

Statistical modeling

Communication

Education

Bachelor's or Master’s in a quantitative field

Tools

PostgreSQL

Job description

SirenOpt is seeking a Data Scientist to join the Applications Engineering team. The role focuses on turning high-dimensional sensor data into actionable material-property predictions, bridging research with production deployment.

You will work forward-deployed with customers, validate models on new materials, and collaborate with software and hardware teams to move models into production.