Job Description

DataVisor is a next-generation security company that utilizes industry leading unsupervised machine learning to detect fraudulent activity for financial transactions, mobile user acquisition, social networks, commerce, and money laundering. Our solution is used by some of the largest internet properties in the world, including Pinterest, FedEx, AirAsia, Synchrony Financial, Tokopedia, Zomato, and Ping An, to protect them from the ever-increasing risk of fraud.

DataVisor holds a rich product portfolio of AI as a platform and other SaaS products, such as feature platform, dEdge, rule engine, case management, and dCube. Our award-winning software is powered by a team of world-class experts in big data, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results driven. Come join us!

As a Fraud Strategy Analyst, (FSA), you are responsible for leveraging our state-of-art fraud detection SaaS products to solve our key clients' fraud and risk problems. You provide technical solutions and consultative services of our state-of-art fraud detection SaaS products to a portfolio of Fortune 500 customers in FinTech, Banking, E-commerce industries. From managing detection system performance to debugging product issues, you are an expert who can provide technical guidance and share best practices with customers on using our Machine Learning models, Rules Engine, and Device Intelligence Signals to detect fraud and risks. You work cross-functionally with Engineering and Product teams to implement new ideas to our analytics solution.

Location: This job is remote-based in Canada.

Specific Job Duties:

• Lead technical discussion for fraud deep dives that prepare for detection modules' success
• Guide and work with our ML modeling team to monitor and enhance the detection quality
• Lead the implementation of detection logics and rules to enhance detection quality
• Provide features and rules writing/debugging type of support for customers' fraud strategy/rule/scientist team
• Build rules and model performance monitoring for internal/external reporting
• Handle data transformation and data joining (by UI or by basic codings)
• Lead training sessions (remote and onsite) for customers on using DV platform for feature and rules writing and detection strategy iterations

• Bilingual in Mandarin and English
• 3+ years of fraud/risk management and fraud analytics experience in banking, payment, social, crypto or e-commerce industries, where machine learning models and/or rules are utilized for fraud prevention of problems
• B.A./B.S. degree in a technical or analytical discipline
• Excellent data analytics skills using tools like SQL, Python, R.
• Great communication and experience explaining methodologies (rule creation, feature creation, model analysis)