Fraud & AML Strategy Co-op, DataVisor
BS/MS Students
Hourly Rate, CAD20-25/hour
ML-powered fraud detection
Be an early applicant
ML-powered fraud detection
101-200 employees
Be an early applicant
Hourly Rate, CAD20-25/hour
101-200 employees
Company mission
To deliver the world’s most sophisticated AI-powered solutions to keep companies and their customers safe from fraud and abuse.
Role
Who you are
- We are looking for curious, analytical, and motivated BS or MS co-op students who are interested in fraud prevention, AML, risk analytics, and strategy design
- This role is ideal for students who enjoy problem-solving, asking “why” and “what if,” and turning data into actionable insights
- Currently enrolled in co-op program or recently completed a Bachelor’s or Master’s degree in:
- Computer Science, Data Science, Engineering, Economics, Business Analytics, Finance, or a related field
- Curious about fraud prevention, AML, risk management, and fintech
- Comfortable working with data and eager to learn industry tools and frameworks
- Able to think analytically and communicate findings clearly
- Canadian Citizen or PR of Canada
- Experience with or coursework in SQL (required)
- Familiarity with Python, data analysis, or statistics through coursework or projects
- Strong analytical and problem-solving skills
- Ability to work independently and collaboratively in a fast-paced environment
Desirable
- Exposure to fraud, AML, payments, or financial services concepts
- Experience with dashboards or analytics tools (e.g., Tableau, Looker, Power BI)
- Understanding of rule-based systems, workflows, or case management concepts
What the job involves
- As a Fraud & AML Strategy Co-op, you will work closely with experienced fraud strategists, data scientists, and product teams to help design, test, and optimize fraud and AML detection strategies across payments, account onboarding, and money movement use cases
- This is a learning-focused role with hands-on exposure to real-world fraud patterns, analytics tools, and decision workflows used by global enterprises
- Fraud & AML Rule Development
- Assist in designing, testing, and tuning fraud and AML detection rules across account origination, transactions, and suspicious activity monitoring
- Help maintain and document rule libraries with proper governance and performance tracking
- Analytics & Experimentation
- Analyze transaction data to identify trends, anomalies, and emerging fraud or AML typologies
- Support experiments and pilot initiatives to test new fraud signals or detection approaches
- Cross-Functional Collaboration
- Partner with Data Science teams to translate fraud patterns into model features
- Work with Fraud & AML Operations teams to review case outcomes and validate detection coverage
- Workflow & Process Support
- Assist in defining fraud and AML workflows, including alerts, queues, and escalation paths
- Help evaluate third-party fraud or AML data sources for enrichment opportunities
- Insights & Reporting
- Contribute to dashboards, reports, and presentations that summarize fraud trends and strategy performance
- Support strategy recommendations for internal stakeholders
Our take
As the use of online shopping and banking continues to rise, so too does the opportunity for fraud, with criminals exploiting the gaps in defences that come with an increasingly novel digital environment. DataVisor provides the leading fraud detection solution that leverages machine learning to identify threats, to overcome the security gap caused by the speed at which today’s digital fraudsters evolve.
Traditional fraud solutions have not been designed to handle digital data, and they are especially ill-equipped to deal with quickly changing environments. By employing advanced ML, DataVisor can identify the patterns which allude to fraudulent behaviour, allowing organisations to respond immediately and prevent losses before they happen. Another problem with some systems has been that, in the name of security, they might delay ultimately good customers from accessing services. With DataVisor this becomes a non-issue, as the pattern of a non-malicious user can also be identified with speed.
DataVisor has seen considerable investment - that will fuel its continued expansion across the globe - and has an impressive list of customers. The company has also made several partnerships that will act towards strengthening its product offering. For example, it is extending its analytics and fraud detection through partnership with Equifax, by gaining access to its rich consumer identity data.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 3 rounds)
Dec 2022
$40m
LATE VC
Feb 2018
$40m
SERIES C
Total funding: $94.5m
Company benefits
- Stock Options
- Commuter Passes
- Paid Time Off
- Catered Lunch and Dinner
- Team and Company Outings
Company HQ
Mountain View, CA
Leadership
Yinglian Xie
(CEO)Extensive experience in security and AI. Previously a Senior Researcher at Microsoft Research.
Fang Yu
(CPO)Former Senior Researcher at Microsoft Research, with vast experience in big-data algorithms.
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