Principal Data Scientist

Principal Data Scientist All the relevant skills, qualifications and experience that a successful applicant will need are listed in the following description. Locations: Scottsdale, AZ | San Francisco, CA | Chicago, IL | New York, NY Hybrid work model –3 days in the office Visa sponsorship not available About the Role We’re working with a leading U.S. financial technology company trusted by major banks and institutions to power secure, real-time payment solutions and identity verification products used by millions of consumers every day. This organization operates at the heart of the U.S. financial ecosystem – enabling instant, safe, and reliable transactions while preventing fraud and maintaining trust across the payments network. They’re now looking for an exceptional Principal Data Scientist to join their growing Data Science organization. In this senior, highly technical role, you’ll lead the design, development, and deployment of advanced machine learning models that power identity and payment systems across a large‑scale, data‑rich environment. You’ll be hands‑on 70–100% of the time – coding, building, and maintaining models in production – while also providing technical leadership, mentoring, and strategic input to help scale data science capabilities enterprise‑wide. What You’ll Do Design, develop, and deploy analytically derived models to assess risk and detect/prevent fraud – across Identity and Payments (ACH) domains. Build end‑to‑end data pipelines and storage schemes for complex, high‑volume datasets using PySpark, Python, and SQL. Collaborate cross‑functionally with Product, Engineering, ML Platform, and Analytics teams to bring models into production and continuously improve them. Drive thought leadership both internally and externally – influencing analytic strategies, evaluating emerging technologies, and representing the company in industry discussions. Lead by example: mentor junior data scientists, guide analytic design, and ensure best practices for scalable model development and deployment. Support multiple projects concurrently , managing timelines, documentation, and technical delivery. What You Bring 10+ years of experience in data analytics or data science in data‑rich environments. 7+ years of hands‑on programming and model development using PySpark, Python, and SQL . 2+ years of direct experience in financial services or fintech . Proven expertise in machine learning, predictive modeling, and optimization – from experimentation to production deployment. Deep familiarity with AWS SageMaker or similar ML platforms. Experience working with financial data and understanding of banking regulations . Strong communicator who can explain complex analytical concepts to both technical and non‑technical stakeholders. Bachelor’s degree in Mathematics, Statistics, Computer Science , or a related field (advanced degree strongly preferred). Preferred Qualifications Advanced degree (Master’s or PhD) in a quantitative field. Experience with scikit‑learn , pandas , and other modern ML libraries. Proven ability to scale teams, processes, and model pipelines within large enterprises. Why Join Work with cutting‑edge data at scale. Collaborate with some of the brightest minds in data science and machine learning . Drive innovation at the intersection of AI, risk management, and financial technology – shaping how consumers and institutions transact safely every day. If you’re a hands‑on data science leader ready to build, deploy, and scale models that impact millions of users daily – we’d love to hear from you. #J-18808-Ljbffr