Research ML Scientist

EnStream LP; Toronto; On-site; CAD 120,000 - 180,000; Full time

Job summary

EnStream LP in Toronto is seeking a Research ML Scientist to lead model development and validation for national-scale digital trust initiatives. This role is hands-on and high-ownership, shaping modeling standards behind a trusted platform.

You will drive R&D across tabular, graph, and foundation models, design validation frameworks, and collaborate with cross-functional teams to meet regulatory requirements.

Qualifications

• Advanced degree (PhD preferred) in Data Science, CS, Statistics, or a related field.
• Experience leading applied ML R&D across tabular, graph, or foundation models.
• Strong background in model validation methodologies in regulated/high-stakes environments.
• Proficiency in Python and standard ML/data science tooling; strong SQL skills.
• Experience taking models from research/prototype to production delivery.
• Ability to work independently and own ambiguous, high-priority initiatives.
• Strong written and verbal communication for regulatory or audit purposes.

Responsibilities

• Lead R&D on fraud and trust-scoring models across tabular, graph, and foundation model approaches.
• Own model validation end-to-end, including designing and running validation frameworks, testing methodologies, and performance benchmarks for regulated contexts.
• Evaluate model architectures for fraud detection and identity trust, balancing performance and interpretability.
• Document model development decisions, validation results, and testing rationale for audit.
• Partner cross-functionally to keep model delivery on track.

Skills

Applied ML R&D

Python

SQL

ML tooling

Communication

Education

PhD or equivalent in Data Science/CS/Statistics

Tools

Graph neural networks

Foundation model tuning

Job description

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’ll Do

• Lead R&D on the progression of our fraud and trust-scoring models across tabular, graph, and foundation model approaches
• Own model validation end-to-end, including designing and running validation frameworks, testing methodologies, and performance benchmarks appropriate for a regulated environment
• Evaluate and recommend model architectures for applicability to fraud detection and identity trust use cases, balancing performance, interpretability, and regulatory requirements
• Document model development decisions, validation results, and testing rationale to support audit and regulatory review
• Partner cross-functionally to keep model delivery on track

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

Ready to Help Build a Safer Canada?

If you’re a systems thinker, trusted advisor, technical storyteller, and mission-driven leader, we’d love to talk.

Who is EnStream EnStream is a trusted leader in secure mobile identity verification and data services in Canada. We work at the intersection of technology, telecommunications, and data privacy — enabling businesses and governments to deliver seamless, secure digital experiences to their customers. Jointly owned by Canada’s largest telecom…

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…