Data Scientist

SirenOpt is hiring a Data Scientist for an on-site, customer-adjacent role on the Applications Engineering team. In this position, you will build and deploy machine learning models that translate complex sensor signals into practical predictions about material properties. You will work on forward-deployed proof-of-concept studies, validate models on novel materials, and partner with software and hardware teams to bring models into production.

What you’ll be doing

• Build, calibrate, and validate predictive models that map sensor signal features to material properties
• Design and evaluate model architectures and featurization strategies for small-data, high-dimensional scientific datasets
• Apply techniques including regression, dimensionality reduction, probabilistic modeling, anomaly detection, and physics-informed ML
• Create testing and validation frameworks that measure performance, including uncertainty quantification and out-of-distribution detection
• Assess model robustness across sample types, process conditions, and instrument configurations
• Prepare models and documentation for handoff to the software engineering team for production deployment
• Analyze datasets from customer proof of concepts and translate findings into model improvement roadmaps
• Compile technical reports and materials to deliver insights to customers
• Collaborate closely with software and hardware engineering teams to move work from research into production

What you’ll bring

• B.S. in Data Science, Statistics, Applied Mathematics, or a related quantitative science field with 3–5 years of applied ML/data science experience, or M.S. with 1–3 years (Ph.D. a plus, not required)
• Hands-on experience building and validating predictive models (supervised and self-supervised) using Python
• Ability to analyze multivariate, high-dimensional datasets and perform feature engineering and selection
• Strong grounding in statistical modeling, including uncertainty quantification, regularization, covariate analysis, and feature importance methods
• Comfort communicating technical findings to both technical and non-technical audiences

Tools you’ll use

Python, PostgreSQL

Benefits

• Equity and salary compensation based on experience
• Health, Dental, Vision plans
• 401(k) matching provided
• 20 days of PTO per year, plus approximately 15 paid US holidays per year

Additional preferences

• Experience with time-series, spectroscopic, or other sensor-based signal data
• Background in manufacturing, materials science, energy storage, semiconductors, or another physical science domain
• Customer-facing or applications engineering experience in a technical product company
• Experience deploying models in production software environments
• Familiarity with data pipeline development (PostgreSQL or similar)
• Fluency in Mandarin Chinese, Japanese, German, Korean, or another key stakeholder language

Location: On-site in San Leandro, CA

Compensation: USD 100,000 - 160,000 per year

Job Type: Full-Time

Minimum experience: 1 year

Education: M.S. or B.S. in Data Science, Statistics, Applied Mathematics, or a related quantitative science field