Job Description
Drive technical roadmap to extend risk monitoring across identified threat surfaces. Develop/experiment/ship state-of-the-art prediction models Use excellent data science practices to iteratively produce high performing models Create immediate impact through sound and practical deliveries of risk monitors Work with engineering colleagues to convey findings through data visualizations Measure, tune and refine existing algorithms to incrementally improve performance Analyze new and existing data after extracting. transforming and combining it in novel ways Convey needs to engineering and operations teams to ensure healthy feedback loops Attract and onboard new talent while preserving and enhancing existing culture Build strong partnerships and collaborate with other teams across the enterprise Demonstrate sense ownership and personal accountability for your team's work Basic Qualifications: 5+ years applied data science experience, including 3 years of advanced analytics experience focused on enterprise-specific problem solving 2+ years management, mentoring, or other closely related team or people leadership experience Experience in machine learning (supervised, semi-supervised or unsupervised learning) Strong communication, delivery management, and leadership skills Preferred Qualifications A bachelor’s degree, MSc or Ph.D. in Statistics, Data Science, Artificial Intelligence, or equivalent alternative education or experience Applied experience with SQL, also Python or R or Scala, and modern data science tools/packages e.g. PyTorch, Transformers, TensorFlow, scikit-learn Applied experience with Databricks and/or Azure ML Strong coding abilities in one or more scripting languages like Python or SQL Understanding of compliance, security, and risk domains along with associated patterns and data elements Understanding of product and services activation, use, and transaction models and data Understanding of statistical analysis and machine learning tools and practi
