Machine Learning Software Engineer

More than a decade ago our founders got started building a new category of products at PayPal and FedEx to protect online retailers from fraud. We found that existing solutions only provided retailers with a cryptic score and relied on human expertise alone to ultimately decide whether or not to accept a transaction. We soon realized online retailers were in need of a simple yes or no decision, but such a product did not exist, and Signifyd was born.

Signifyd is seeking machine learning engineers to join our engineering team. The ideal candidate will have both a machine learning background and software engineering skills. Industry experience working on a range of classification and optimization problems, e.g. payment fraud, click-through rate prediction, click-fraud detection, etc. will be highly desirable. The position will involve taking these skills and experiences and applying them to the fraud domain to combat online transaction fraud and make the world of e-commerce a better place.

* Develop classifiers and tools leveraging machine learning, data regression, and rules-based models * Develop tools and system for model comparison and A/B testing * Suggest, identify and synthesize requirements and create effective feature roadmap * Apply expert software development skills to a wide range of ML-related coding projects

* MS degree in Computer Science or related quantitative field with 5 years of relevant experience or Ph.D degree in Computer Science or related quantitative field * Experience in one or more of the following areas: machine learning, large-scale data mining or artificial intelligence. * Proven ability to translate insights into business recommendations * Knowledge of payment fraud is highly desirable * Experience with Spark/Hadoop is a plus * Experiences with AWS infrastructure is a plus * Experience developing and debugging in Java/Clojure/Scala, Knowledge of functional programming is a plus * Experience with scripting languages such as Perl, Python, and shell scripts