DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's solution scales infinitely and enables organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide guaranteed performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.
Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!
What You’ll Do
- Build and enhance real-time anti-fraud systems processing large-scale data.
- Develop and optimize backend services, internal tools, and validation frameworks.
- Contribute to distributed system components across multi-region cloud environments.
- Use big-data technologies (Spark, Hadoop, ClickHouse, Yugabyte) to build scalable pipelines.
- Build real-time data workflows using Kafka, Flink, and related technologies.
- Maintain development, testing, and delivery frameworks with a focus on quality and scalability.
Requirements
- Strong CS fundamentals (data structures, algorithms, OS, networking).
- Proficiency in Java/Spring for backend development.
- Experience with MySQL and SQL optimization.
- Basic system design skills (scalability, reliability, performance).
- Familiarity with testing, automation, and CI/CD.
- Strong communication skills and a collaborative mindset.
Preferred Qualifications
- Experience with messaging systems (Kafka or similar).
- Familiarity with analytical/distributed databases (ClickHouse, YugabyteDB).
- Exposure to big-data frameworks (Spark, Flink).
- Basic understanding of ML concepts and modern AI/LLM tools.
- Experience with Kubernetes and cloud platforms (preferably AWS).
- Ability to write automation scripts (Bash, Python).
Benefits
- Hands-on experience in a dynamic and collaborative work environment.
- Opportunity to work closely with experienced professionals in the field.
- Exposure to real-world software testing scenarios.
- Competitive hourly rate, range 20-25 CAD per hour.
United States