Fraud Data Scientist

Job Title: Fraud Data 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 accelerating two high-priority fraud detection and prevention initiatives and need a hands-on Fraud Data Scientist. This role sits at the intersection of investigative analysis, applied data science, and cross-functional communication — turning raw fraud signals into actionable intelligence for internal teams, partners, and the broader digital trust roadmap. You will be running on hypercare support, creating fraud intelligence reporting, and building the analytical foundation for ongoing fraud protection R&D. What You’ll Do Serve as front-line analytical support during hypercare for two new fraud protection initiatives, responding directly to client and external partner requests, such as detailed fraud case analysis Triage, investigate, and resolve incoming fraud-related queries within defined SLAs during the critical post-launch period Analyze fraud patterns across categories and typologies to identify emerging trends, gaps in coverage, and opportunities for improvements of fraud detection capabilities Translate analytical findings into concrete recommendations that inform R&D priorities Generate and disseminate fraud intelligence reports to external data-sharing partners on a recurring and ad hoc basis while ensuring that reports are accurate, timely, and actionable for external partners with varying levels of technical sophistication. Build and maintain fraud data products (datasets, dashboards, tools) that support ongoing external partner operations and future roadmap of digital trust products Partner cross-functionally with engineering, product, and partner-facing teams to ensure fraud data products are accurate, scalable, and production-ready. What You Bring Must-Have Skills & Experience Bachelor's degree in Data Science, Statistics, Computer Science, Economics, or a related quantitative field (or equivalent practical experience) Demonstrated experience in fraud analytics, risk analytics, or a related investigative/adversarial data domain. Strong SQL skills and proficiency in a data science programming language (Python) Experience analyzing large, messy, real-world datasets to identify patterns and anomalies Ability to communicate technical findings clearly to both technical and non-technical audiences, including external partners Comfort operating in an ambiguous, fast-moving environment with evolving requirements Preferred Qualification Experience with entity resolution, identity graph analysis Prior experience supporting a product launch or hypercare period Experience building or maintaining data pipelines, feature stores, or ML-based detection models Background in financial crimes, trust & safety, cybersecurity, or adjacent risk domains 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 highly skilled, cross-functional team

The role involves providing front-line analytical support for fraud protection initiatives and investigating fraud patterns to identify emerging trends. You will create fraud intelligence reports and build data products to support external partners and the digital trust roadmap.

Candidates must have a bachelor's degree in a quantitative field and demonstrated experience in fraud or risk analytics using SQL and Python. Proficiency in analyzing large, messy datasets and communicating technical findings to diverse audiences is required.

• SQLPreferred
• Data analysisPreferred
• Machine learningPreferred
• PythonPreferred

Identified from the job description. Confirm important requirements above.

• Fraud Analytics
• Risk Analytics
• SQL
• Python
• Data Analysis
• Machine Learning
• Deep Learning
• Entity Resolution
• Identity Graph Analysis
• Data Pipeline Construction
• Feature Stores
• Technical Communication
• Fraud Case Analysis
• Reporting
• Triage
• Investigative Analysis

• Data & Analytics
• Technology
• Security & Safety
• Software
• Engineering

Minimum education

Bachelor’s degree

Minimum experience

2+ years

Apply by

Jan 12, 2027

Posting language

English

Working hours

40 hours per week

Office presence

4 days per week

Seniority

Entry level

Application method

Direct apply is available