Data Scientist

A successful Data Scientist in Fraud & Credit Risk - Decision Science at Fiserv plays a pivotal role in the Global Business Solutions (Merchant business) team. The main responsibilities include developing and deploying predictive ML models to automate risk controls, reduce fraud and credit risk losses, and drive top-line growth. The efforts of the Data Scientist generate insightful analytics, build models/rules, and create data-driven solutions to manage risk and identify new opportunities. This position interfaces with internal and external stakeholders to deliver best-in-class analytical solutions and supports functions such as New Merchant On-boarding & Underwriting, Existing Merchant Risk Monitoring, and more. The key responsibilities of the Data Scientist include developing and deploying ML/predictive models using internal and external data, tracking and monitoring model performance, conducting complex analysis using statistical and quantitative techniques, evaluating and integrating data from various sources for modeling, analytics, and reporting, generating insights from data to assess key performance indicators/trends, partnering with business and technical Subject Matter Experts (SMEs) to analyze and solve business problems, supporting the transformation of risk data capabilities through advanced technology and real-time decision-making, implementing models and decision rules in production with IT/deployment teams, developing documentation to meet internal and external stakeholder requirements, and coaching junior team members and overseeing project delivery. The ideal candidate for this role should possess a Bachelor's degree in Mathematics, Statistics, Computer Science, Engineering, or a related field, along with 7+ years of experience in risk/marketing data analytics or predictive modeling. Proficiency in SQL, Python, SAS, or other analytical tools/open-source programming languages, strong technical skills, problem-solving ability, excellent communication, and interpersonal skills are also required. Additionally, having a Master's degree in a relevant field, 10+ years of experience, experience with credit bureaus and other external data sources, and hands-on experience with AI/Money Laundering techniques would be considered great assets for this position.,