Research ML Scientist

Job Title: Research ML Scientist

Department: Data and AI

Type: Full-Time

Reports to: Head of Applied AI & Data Engineering

This role requires a minimum of four (4) days per week working onsite at EnStream’s head office in Toronto; this requirement may be changed at management’s discretion.

Who is EnStream

EnStream is a leader in secure digital identity and mobile data intelligence, working to advance the future of digital trust in Canada. We build innovative data-driven models that enhance the integrity, reliability, and safety of digital identity ecosystems. Our latest initiative leverages advanced data science, machine learning, and deep learning to further grow and sustain digital trust across Canada.

Our mission is to empower frictionless trust in every interaction. EnStream is dedicated to increasing trust and convenience for Canadians using real-life, verified identities and network data held by trusted telco networks. At EnStream, every team member plays a critical role in shaping our strategy and delivering meaningful impact across industries.

About the Role

We're building critical R&D and validation runway for our next-generation fraud and trust-scoring models - spanning tabular, graph, and foundation model. The Research ML Scientist to lead model R&D and own model validation end-to-end. This is a hands-on, high-ownership role for someone who wants to shape the modeling and validation standards behind a national-scale digital trust platform.

What You Bring

Must-Have Skills & Experience

• Advanced degree (PhD preferred) in Data Science, Computer Science, Statistics, or a related quantitative field, or equivalent practical experience
• Demonstrated experience leading applied ML R&D, ideally spanning tabular models, graph-based models, and/or foundation models
• Strong background in model validation methodologies, particularly within regulated or high-stakes environments
• Proficiency in Python and standard ML/data science tooling; strong SQL skills
• Experience taking models from research or prototype stage through to production-grade delivery
• Ability to work independently and take ownership of ambiguous, high-priority initiatives under time pressure
• Strong written and verbal communication skills, including documenting technical decisions for regulatory or audit purposes

Preferred Qualifications

• Experience in fraud detection, identity, or digital trust domains
• Experience with graph neural networks or graph-based feature engineering
• Familiarity with foundation model fine-tuning or adaptation for tabular or graph data
• Experience operating within a regulated industry (financial services, telecom, or similar) 

Why Join Us?

• Contribute to a national-scale initiative defining the future of digital trust in Canada
• Work on cutting-edge fraud detection applications using real-world identity data
• Collaborate with a lean, highly skilled team where your work has outsized impact on the roadmap