Fraud Data Scientist generating insights using statistical analysis and machine learning for UMB's fraud initiatives. Involves collaboration across teams to enhance fraud detection models.
Responsibilities
Work closely across the organization to develop and implement statistical analysis, artificial intelligence, machine learning processes and algorithms, and deep learning for fraud modeling
Use dynamic techniques like Machine Learning to gain insights about the future
Answer the “What will happen, and What should be done?” questions
Gather business detail from peers and internal customers to adapt/enhance models
Routinely measure model performance and implement modifications as needed
Requirements
Master’s Degree in Computer Science, Math, Economics, Statistics, or another quantitative field and 2+ years of unsupervised data modeling and segmentation experience OR any combination of education and experience that would provide an equivalent background
Proven expert level foundation of math, statistics, and programming
Demonstrated hands-on working knowledge of R or Python, Snowflake, SQL Server or similar database management tool and visualization tools such as Tableau or Power BI
Superior critical thinking skills
Strong proficiency in statistical algorithm development and evaluation
Proficiency in advanced statistics, hyperparameter tuning, A/B Testing, predictive modeling, recommendation systems, propensity scoring, natural language processing, clustering, customer segmentation, data acquisition, mining structured and unstructured data, designing tools, automation systems, and data frameworks
Benefits
Paid Time Off
401(k) matching program
Annual incentive pay
Paid holidays
Comprehensive company sponsored benefit plan including medical, dental, vision, and other insurance coverage
Health savings, flexible spending, and dependent care accounts
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