Lead Data Scientist

Company

Sixone’s mission is to enable a world where blended plastics products can be circularly recycled back into existing supply chains instead of being sent to landfill. Sixone is developing technologies to enable advanced recycling of blended plastics and plastic-based products. The company’s technology applies process digitalization and advanced analytics to build a depolymerization reactor tailored to enable efficient plastics recycling. The company aims to fundamentally change the economics behind current recycled materials through advanced processing and materials technologies.

Overview of Role

This role focuses on applying data science and machine learning techniques to make real-time sorting and process decisions. You will lead a small team of talented data scientists to build robust representations of materials from high-dimensional sensor data, and turning them into models that run reliably.

This is a hybrid role that requires a consistent in-office presence four days per week.

Responsibilities

• Lead architectural decisions for Sixone’s ML systems by translating scientific and product requirements into scalable, maintainable system designs.
• Develop and benchmark novel deep learning architectures for high-dimensional spectral data, including classification, segmentation, anomaly detection, and representation learning.
• Build and manage data pipelines in Python and SQL, locally and on AWS, integrating data from a variety of imaging and edge-sensing devices, including proprietary formats and calibration workflows.
• Lead, mentor, and grow a team of data scientists.
• Drive work planning, prioritization, and resource allocation against short- and long-term objectives.
• Partner with Engineering, R&D, and Production teams to move models from lab to pilot to production scale.
• Maintain documentation standards for experiments, data workflows, and models that support IP protection, compliance, and knowledge retention.
• Stay current with the state of the art in ML for sensing and imaging, and bring relevant methods into the team.

Candidate Requirements

• 4+ years in data science or applied ML research with a focus on computer vision or spectral/sensor data
• Demonstrated technical leadership
• Master's or Ph.D. in Computer Science, Electrical Engineering, Physics, or a related quantitative field or equivalent practical experience.
• Experience with representation learning on high-dimensional sensors: autoencoders, self-supervised learning, dimensionality reduction, and sensor preprocessing/calibration.
• Experience in Python and SQL, with a track record of taking models from research prototype to production.
• Hands-on PyTorch experience (CNNs, Vision Transformers, and autoencoders) and computer vision libraries such as OpenCVPractical experience with pytest, Docker, CI/CD pipelines, and experiment tracking (MLflow or similar)
• Effective communication skills with both technical and non-technical stakeholders.
• Legally entitled to work in Canada.

Preferred Skills

• Hyperspectral imaging experience: spectral unmixing, band selection, sensor calibration, HSI data formats.
• NIR/SWIR spectroscopy or chemometrics
• Multi-sensor fusion; edge/real-time deployment (ONNX, TensorRT, embedded inference).
• ML for industrial inspection, sorting, or manufacturing systems.

Sixone offers a stimulating work environment that promotes creativity, curiosity, and innovation. Join the team and contribute to our mission to transform the recycling industry and promote a sustainable future!