Job Description Are you ready to shape the future of Data Science innovation? Do you thrive on building cutting-edge, scalable analytical solutions? Equifax Workforce Solutions is seeking a visionary Data Scientist to join our dynamic Data & Analytics team. If you are a tech-savvy leader passionate about designing and developing powerful Machine Learning solutions—blending science, art, and keen business logic to unlock the true potential of data—we want you to help solve complex business problems and drive financial wellness for millions. In this high-impact role, you will be critical to pioneering Data Science initiatives, collaborating closely with stakeholders across Sales, Product, and Technology. You will leverage your expertise to explore consumer personas, showcase the unique value of The Work Number dataset, and make a tangible impact on product innovation. This is an exceptional opportunity to accelerate your career at one of the largest global data analytics and technology companies. This role requires being in the office 3 days/week on Tues - Thurs. This position does not offer immigration sponsorship (current or future) including F-1 STEM OPT extension support. What you will do: • For the first 3-6 months you will learn our data, our technologies, our platform and work on exciting projects to support our advanced analytics team. • You will design, develop, and implement advanced machine learning models specifically for delinquency prediction, focusing on utilizing income and employment data, and supporting credit policy optimization strategy across various financial products and services. • You will conduct thorough analysis of large datasets, with an emphasis on income, employment history, and related financial data, to identify anomalies, patterns, and conduct feature engineering for continuous model improvement and credit risk assessment. • You will utilize a variety of statistical and machine learning techniques relevant to credit risk management and fraud detection, including classification and regression algorithms (e.g., logistic regression, decision trees, random forests, gradient boosting, neural networks). • You will work with key clients on custom projects and solutions through the development of custom scores, strategy optimization, benchmarking and reporting reports and co-innovation projects. • You will effectively communicate analytical results to key stakeholders using strong data visualizations, superior presentation skills and business language to emphasize the “so what” of any analysis performed. • You will stay current with the latest trends and techniques in risk management, machine learning, and the evolving landscape of credit policies. What experience you will need: • 5+ years’ data science experience with expert knowledge of Python, SQL, R or SAS in a large data environment. • 3+ years’ experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks (including LSTMs, RNNs). • Proven track record of designing and developing predictive models in real-world applications. • Experience with model performance evaluation and predictive model optimization for accuracy and efficiency. • Bachelor’s or advanced degree in a quantitative discipline such as Engineering, Economics, Mathematics, Statistics, or Physics is essential. What could set you apart (nice to have skills): • Strong problem-solving skills with a critical and analytical mindset to address ambiguous client challenges. • Knowledge of the financial services industry. • Experience in building, loading, transforming, and analyzing data within Google Cloud Platform (GCP) or similar major cloud environments (AWS/Azure). • Work experience using AI/Generative AI tools (e.g. Gemini, CoPilot) to accelerate workflow, improve code efficiency, or identify novel insights. #LI-SM1 #LI-Hybrid