PLEASE APPLY IN ENGLISHThe Data Science team builds production machine learning models that are the core of Signifyd's product.Our product helps businesses of all sizes minimize their fraud exposure and grow their sales. This translates into improved e-commerce shopping experience for individuals, by reducing the number of orders that are incorrectly declined, and by making account hijacking less profitable for criminals.The data science team has end-to-end ownership of our decision engine, from research and development to online performance and risk management.We value collaboration and team ownership -- no one should feel they're solving a hard problem alone.Together we help each other grow our skills through peer reviews, group studies, and frequent knowledge sharing to deepen our ML and stats understanding. This is done through live demos, write-ups, and special cross-team projects.The Data Science and Engineering teams at Signifyd have always had a strong contingent of remote folks, individual contributors and team leads. The challenges of working remotely aren't new to us and we strive to iteratively improve our remote culture.We are looking for someone who embodies our company values:Curious and Hungry: Be willing to do research and design experiments by being hands-onTenacious: Creating something new is hard work, and our Data Scientist team never gives upCustomer Passion: Be the backbone to our platform, and help us stay ahead of fraudstersDesign for Scale: Work with the rest of the Data Science team to make fraud protection at scale possibleAgile: Some days you may spend doing research and designing experiments while others are spent using your analytical toolbox to surface insights into real-time fraud attacks.Roll Up Your Sleeves: Partner closely internally to learn from others, and succeed as a teamHow you’ll have an impact:Building production machine learning models that identify fraudWriting production and offline analytical code in PythonWorking with distributed data pipelinesCommunicating complex ideas effectively to a variety of audiencesCollaborate with engineering teams to strengthen our machine-learning platformRequirements:Bachelor's degree in computer science, applied mathematics, economics, or an analytical field or equivalent practical experienceAt least 5+ years of experienceBuilding production ML modelsHands-on statistical analysis with a solid fundamental understandingDesigning experiments and collecting dataWriting code and reviewing others’ in a shared codebase, preferably in PythonPractical SQL knowledgeFamiliarity with the Linux command lineFluent in EnglishThis role has on-call shifts, as part of our weekend rotation, Fri/Sat/Sun. While the number of shifts is subject to change, currently it works out to about six weekends a year.Bonus points if you haveAdvanced degree in an analytical field (Master, PhD)Previous work in fraud, risk, payments, or e-commerceWorked previously with Go-to-Market teams directlyData analysis experience in a distributed environmentPassion for writing well-tested production-grade codeCheck out how Data Science is powering the new era of EcommerceCheck out our Director of Data Science featured in Built InWe want to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.Signifyd's Applicant Privacy Notice
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