Software Engineer, DataVisor
Co-Op Internship Winter 2025
More information about location
ML-powered fraud detection
Open for applications
ML-powered fraud detection
101-200 employees
Open for applications
More information about location
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 creative and eager-to-learn engineers to help us expand our novel streaming and database systems, which enable our detection capabilities
- This position is ideal for those who are majoring in Computer Science or Computer engineering who would like to gain some hands-on experience in fraud detection and machine learning before graduation
- This internship could lead to a full-time position after graduation
- BS/MS students majoring in Computer Science, Engineering or a related subject, Current Co-op students or students enrolled in a post-secondary program (BS or MS) who are majoring in computer science, information management, or a related field of Canada Canada-based college or university.ideally in his/her last school year
- Proven working experience in Java, Shell, Python development
- Excellent knowledge of Relational Databases, SQL and ORM technologies (JPA2, Hibernate) is a plus
- Experience in Cassandra, HBase, Flink, Spark or Kafka is a plus
- Experience in the Spring Framework is a plus
- Experience with test-driven development is a plus
- Strong communication and interpersonal skills
What the job involves
- As a platform engineer intern, you will learn how to build a next-generation machine learning platform, which incorporates our secret sauce, UML (unsupervised machine learning) with other SML (supervised machine learning) algorithms
- Our team works to improve our core detection algorithms and automate the full training process
- As complex fraud attacks become more prevalent, it is more important than ever to detect fraudsters in real-time
- The platform team is responsible for developing the architecture that makes real-time UML possible
- Design and build machine learning systems that process data sets from the world’s largest consumer services
- Use unsupervised machine learning, supervised machine learning, and deep learning to detect fraudulent behavior and catch fraudsters
- Build and optimize systems, tools, and validation strategies to support new features
- Help design/build distributed real-time systems and features
- Use big data technologies (e.g. Spark, Hadoop, HBase, Cassandra) to build large scale machine learning pipelines
- Develop new systems on top of realtime streaming technologies (e.g. Kafka, Flink)
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
Few candidates hear
back within 2 weeks
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 values
- Take a results-driven approach.
- Prioritise team spirit and hard work.
- Be honest, curious, and maintain the highest levels of integrity.
Company HQ
Mountain View, CA
Articles
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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