Data Scientist

The Data Science team creates operational machine learning models that constitute the core of Signifyd's product. We assist companies of all sizes in reducing their fraud exposure and boosting their revenues. We also enhance the online shopping experience for individuals by decreasing the number of incorrectly rejected orders and making account hijacking less lucrative for criminals. The team has complete control of our decision-making engine, spanning from research and development to online performance and risk management. We value teamwork and mutual ownership - no one should feel like they're tackling a difficult challenge alone. Together, we support each other in developing our abilities through peer evaluation of experiments and code, group study sessions to enhance our understanding of ML and statistics, and regular sharing of knowledge through live demonstrations, write-ups, and special inter-team projects. The Data Science and Engineering team at Signifyd has always had a strong remote workforce, including individual contributors and team leaders. The hurdles of remote work are not new to us, and we have gradually improved our remote work culture. How you'll make an impact: - Research new, real-time fraud patterns with our Risk Intelligence team. - Enhance the key components of the Signifyd Commerce Protection Platform. - Communicate complex concepts to a broad audience. - Develop operational machine learning models to detect fraud. - Write production and offline analytical code in Python. - Work with distributed data pipelines. - Collaborate with engineering teams to fortify our machine learning pipeline. Requirements: - A computer science degree or a similar analytical field, or equivalent practical experience. - Minimum 2 years of relevant job experience. - Use visual representations to communicate analytical results to team members. - Conduct hands-on statistical analysis with a strong fundamental understanding. - Write code and review others’ code in a shared codebase, preferably in Python. - Practical knowledge of SQL. - Experience in designing experiments and collecting data. - Familiarity with the Linux command line. - This role involves on-call shifts as part of our weekend rota; currently, it amounts to about six weekends a year. Bonus points if you have: - Previous experience in fraud, payments, or e-commerce. - Experience in data analysis in a distributed environment. - Passion for crafting well-tested production-grade code. - A Master's Degree or PhD. Check out how Data Science is powering the new era of Ecommerce and explore our Director of Data Science featured in Built In. Signifyd offers all its employees a base salary, bonus, equity, and benefits. Our advertised job may cover more than one career level, and the level and salary offered will be determined by the candidate's specific experience, knowledge, skills, and abilities, and internal equity and alignment with market data.