It’s been over a decade since Drew Conway published his data science venn diagram, wherein he highlighted hacking skills, mathematical and statistical knowledge, and domain expertise as critical to success and career progression in the field. Increasingly, companies are seeing that this combination of competencies is also critical to the success of data science projects, which benefit strongly from interdisciplinary collaboration. Here, Adam Inzelberg (decision scientist) and Ilan Voronel (data scientist) describe how they collaborated to build two fraud detection systems (using supervised graph linking based clustering and unsupervised models).