Senior Data Scientist, Predict

Alloy is where you belong! Alloy helps solve the identity risk problem for companies that offer financial products by enabling them to outpace fraud and confidently serve more people around the world. Over 800 of the world’s largest financial institutions and fintechs turn to Alloy to take control of fraud, credit, and compliance risk, and grow with the clearest picture of their customers. Through our values: Be Bold, Get Scrappy, Collaborate, and Celebrate Our Differences, we are creating a workplace where you can grow, thrive, and belong. See how we’ve been continuously recognized and named one of Inc. Magazine’s Best Workplaces , Forbes America’s Best Startup Employers , Best Fintech to Work for by American Banker , year after year. Check out our investors and read more about us here . About the team The Predict team builds Alloy’s real-time machine learning systems at scale. Our immediate focus is on fraud detection, where we believe machine learning can simplify and accelerate decision-making in ways traditional rule-based systems can’t. Managing rules and policies to detect fraud is complex and constantly evolving; we use ML to make it smarter, faster, and more adaptive. Our approach is identity-centric, combining signals from a wide range of data sources to build a comprehensive understanding of risk. You will work on advancing our core models while also partnering directly with customers to drive strong outcomes from fraud studies. Alloy operates in a hybrid work environment. We look to foster collaboration and community by having our local employees onsite three days a week. What you'll be doing Contribute to the design, training, and evaluation of machine learning models that power Alloy’s fraud detection capabilities. Develop testing plans, metrics, performance reports, and translate findings into actionable recommendations. Support production ML workflows, including feature generation, model training, and monitoring, to ensure models remain accurate and reliable at scale. Document findings and communicate insights to internal teams, contributing to shared learning and continuous improvement. Maintain up-to-date model documentation and support Alloy’s model governance processes to ensure transparency and compliance. Stay current with industry trends in applied ML and fraud detection, and contribute to Alloy’s mission of making financial services safer and more accessible. Who we’re looking for Always building with end-solution in mind. Able to communicate complicated concepts to a non-technical audience without diluting the complexity of the work. Able to build strong cross-functional relationships within Alloy. Naturally curious with a knack for asking tough questions. Solid understanding of core ML concepts such as supervised learning, feature engineering, and model evaluation. A team player. You believe that big things happen when the right people are working together. A fast learner Humble. Mistakes happen and owning them helps us learn and move on quickly You have: 8+ years as an individual contributor in Applied Fraud Research, Data Science, or Machine Learning with a proven track record in a “Solutions” or client-facing capacity. Expertise in working with highly imbalanced datasets and building production-grade Machine Learning models with specific interest in tree-based models. Advanced proficiency in scripting languages like Python and querying languages like SQL Proven ability to wrangle and think thoughtfully about data at scale (processing billions of records). Experience developing metrics and dashboards. Able to communicate their findings effectively to technical and nontechnical members Someone who embodies our shared Alloy values: be bold, get scrappy, collaborate, and celebrate our differences. You have experience in a highly analytical role in fast-paced environments Must be local to Greater New York City. Nice to Haves: Previous experience in financial fraud detection. Advanced Degree (Masters or