Data Scientist - Fraud Analytics - COLORADO SPRINGS

- Bachelors degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or a related quantitative discipline; OR 4 years of relevant experience in statistics or quantitative analytics may substitute for a degree. - Minimum 2 years of experience in predictive analytics or data analysis, OR an advanced degree (e.g., Masters, PhD) in a quantitative field. - Proficiency in training and validating statistical, physical, machine learning, and other complex analytics models. - Experience with a multifaceted scripting language (such as Python or R) for statistical analyses and AI/ML model development. - Strong coding skills focusing on clarity, detailed documentation, and logical explanations (high code transparency). - Competence in querying and preprocessing data from structured and unstructured sources using languages such as SQL, HQL, or NoSQL. - Familiarity with handling structured, semi-structured, and unstructured data files, including delimited numeric data, JSON/XML, and text documents. - Understanding of classical supervised modeling techniques like linear/logistic regression, discriminant analysis, and decision trees. - Knowledge of unsupervised modeling concepts such as k-means clustering and hierarchical clustering. - Strong communication skills for presenting analytical and modeling results to non-technical stakeholders.