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 RoleWe'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 DoLead R&D on the progression of our fraud and trust-scoring models across tabular, graph, and foundation model approachesOwn model validation end-to-end, including designing and running validation frameworks, testing methodologies, and performance benchmarks appropriate for a regulated environmentEvaluate and recommend model architectures for applicability to fraud detection and identity trust use cases, balancing performance,



interpretability, and regulatory requirementsDocument model development decisions, validation results, and testing rationale to support audit and regulatory reviewPartner cross-functionally to keep model delivery on trackWhat You BringMust-Have Skills & ExperienceAdvanced degree (PhD preferred) in Data Science, Computer Science, Statistics, or a related quantitative field, or equivalent practical experienceDemonstrated experience leading applied ML R&D, ideally spanning tabular models, graph-based models, and/or foundation modelsStrong background in model validation methodologies, particularly within regulated or high-stakes environmentsProficiency in Python and standard ML/data science tooling; strong SQL skillsExperience taking models from research or prototype stage through to production-grade deliveryAbility to work independently and take ownership of ambiguous, high-priority initiatives under time pressureStrong written and verbal communication skills, including documenting technical decisions for regulatory or audit purposesPreferred QualificationsExperience in fraud detection, identity,



or digital trust domainsExperience with graph neural networks or graph-based feature engineeringFamiliarity with foundation model fine-tuning or adaptation for tabular or graph dataExperience 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 CanadaWork on cutting-edge fraud detection applications using real-world identity dataCollaborate with a lean, highly skilled team where your work has outsized impact on the roadmapReady 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 bechanged 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 cutting-edge data-driven models that enhance the integrity, reliability, and safety of digital identity ecosystems. Our latest initiative leverages advanced data science, machine... #J-18808-Ljbffr

📌 Research Ml Scientist (Toronto)
🏢 EnStream
📍 Toronto