Data Scientist

About the role

VoltForce is collaborating with a pioneering materials-inspection firm to find a Data Scientist. This position focuses on enhancing the manufacturing of micro- and nano-scale materials, which are essential for critical industries such as energy storage, aerospace, and semiconductors. The role involves utilizing advanced machine learning techniques to convert complex sensor data into actionable insights for manufacturers.

Key facts

What you'll do

• Develop and fine-tune machine learning models that correlate sensor data with material characteristics.
• Create and assess innovative model architectures and feature extraction methods tailored for scientific datasets with limited samples.
• Implement various techniques such as regression, dimensionality reduction, and anomaly detection within a physics-informed machine learning framework.
• Establish testing and validation protocols to ensure model performance, including uncertainty analysis and detection of out-of-distribution samples.
• Evaluate model stability across different sample types and manufacturing conditions.
• Prepare models and necessary documentation for transition to the software engineering team for production use.
• Analyze data from customer proof-of-concept projects and prepare technical reports for clients.
• Transform insights and feedback from stakeholders into actionable plans for model enhancements.

Requirements

• Bachelor's degree in Data Science, Statistics, Applied Mathematics, or a similar quantitative discipline with 3 to 5 years of relevant experience in machine learning or data science; or a Master's degree with 1 to 3 years of experience (Ph.D. is a plus, but not mandatory).
• Practical experience in developing and validating predictive models (both supervised and self-supervised) using Python.
• Proficiency in analyzing complex, high-dimensional datasets, along with skills in feature engineering and selection.
• Strong understanding of statistical modeling techniques, including uncertainty quantification and feature importance analysis.
• Excellent communication skills, capable of presenting technical information to diverse audiences.

Nice to have

• Familiarity with time-series, spectroscopic, or sensor-based signal data.
• Experience in manufacturing, materials science, energy storage, semiconductors, or related physical science fields.
• Background in customer-facing roles or applications engineering within a technical product environment.
• Experience in deploying models in production settings.
• Knowledge of data pipeline development, particularly with PostgreSQL or similar systems.
• Proficiency in Mandarin Chinese, Japanese, German, Korean, or another relevant language.

It's acceptable if you don't meet every requirement. We value curiosity, analytical rigor, and a willingness to learn.

Equal Opportunity Statement

We are dedicated to fostering diversity and inclusivity in our workplace.