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Signifyd is a fraud detection and risk management platform trusted by thousands of merchants across 100+ countries, processing billions of transactions annually. The Applied Decision Science (ADS) team builds production machine learning models and risk management tools that form the core of Signifyd's product, helping businesses minimize fraud exposure while improving the e-commerce experience for legitimate customers.
As a Data Scientist II, you will be a full-stack operator responsible for end-to-end development, deployment, and evaluation of ML models that assess transaction risk. You'll partner with Business Unit Leads to identify gaps in decisioning performance and implement solutions with guidance from senior team members. Key responsibilities include building and improving production ML models for fraud detection in collaboration with other data scientists and ML engineers, running experiments to optimize decisioning strategies, identifying and building automation to reduce manual work, and communicating complex technical ideas to diverse audiences including Customer Success, Sales, and external customers.
You'll write production and offline analytical code in Python, work with distributed data pipelines using Spark, Databricks, and GCP, and design experiments to validate hypotheses. The role includes on-call shifts as part of a weekend rotation (approximately six weekends per year). Signifyd emphasizes collaboration and peer learning through code review, group study sessions, and knowledge-sharing across the team. The company is remote-first with most staff working remotely; there is no travel requirement. The team actively uses generative AI tools and values strong communication skills alongside technical depth.
