Job
Description
Role Overview: As a Data Scientist in Fraud & Credit Risk - Decision Science at Fiserv, you will play a pivotal role in the Global Business Solutions (Merchant business) team. Your main responsibility will be to develop and deploy predictive ML models that automate risk controls, reduce fraud and credit risk losses, and drive top-line growth. You will generate insightful analytics, build models/rules, and create data-driven solutions to manage risk and identify new opportunities. This role involves collaborating with internal and external stakeholders to deliver best-in-class analytical solutions and support functions including New Merchant On-boarding & Underwriting, Existing Merchant Risk Monitoring, and more. Key Responsibilities: - Develop and deploy ML/predictive models using internal and external data. - Track and monitor model performance and provide analytical support for business decisions. - Conduct complex analysis using statistical and quantitative techniques. - Evaluate and integrate data from various sources for modeling, analytics, and reporting. - Generate insights from data to assess key performance indicators/trends. - Partner with business and technical Subject Matter Experts (SMEs) to analyze and solve business problems. - Support the transformation of risk data capabilities through advanced technology and real-time decision-making. - Implement models and decision rules in production with IT/deployment teams. - Develop documentation to meet internal and external stakeholder requirements. - Coach junior team members and oversee project delivery. Qualifications Required: - Bachelor's degree in Mathematics, Statistics, Computer Science, Engineering, or related field. - 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 and problem-solving ability. - Excellent communication and interpersonal skills. Additional Company Details: Experience with credit bureaus and other external data sources would be beneficial. Hands-on experience with AI/Money Laundering techniques is a plus. It would be great to have a Master's degree in Mathematics, Statistics, Computer Science, Engineering, or related field, and 10+ years of relevant experience. Role Overview: As a Data Scientist in Fraud & Credit Risk - Decision Science at Fiserv, you will play a pivotal role in the Global Business Solutions (Merchant business) team. Your main responsibility will be to develop and deploy predictive ML models that automate risk controls, reduce fraud and credit risk losses, and drive top-line growth. You will generate insightful analytics, build models/rules, and create data-driven solutions to manage risk and identify new opportunities. This role involves collaborating with internal and external stakeholders to deliver best-in-class analytical solutions and support functions including New Merchant On-boarding & Underwriting, Existing Merchant Risk Monitoring, and more. Key Responsibilities: - Develop and deploy ML/predictive models using internal and external data. - Track and monitor model performance and provide analytical support for business decisions. - Conduct complex analysis using statistical and quantitative techniques. - Evaluate and integrate data from various sources for modeling, analytics, and reporting. - Generate insights from data to assess key performance indicators/trends. - Partner with business and technical Subject Matter Experts (SMEs) to analyze and solve business problems. - Support the transformation of risk data capabilities through advanced technology and real-time decision-making. - Implement models and decision rules in production with IT/deployment teams. - Develop documentation to meet internal and external stakeholder requirements. - Coach junior team members and oversee project delivery. Qualifications Required: - Bachelor's degree in Mathematics, Statistics, Computer Science, Engineering, or related field. - 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 and problem-solving ability. - Excellent communication and interpersonal skills. Additional Company Details: Experience with credit bureaus and other external data sources would be beneficial. Hands-on experience with AI/Money Laundering techniques is a plus. It would be great to have a Master's degree in Mathematics, Statistics, Computer Science, Engineering, or related field, and 10+ years of relevant experience.
