Data Scientist II - Fraud, Cutting-Edge Technologies

- Bachelor’s degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, engineering, or other related quantitative disciplines; alternatively, 4 years of experience in statistics, mathematics, or quantitative analytics may replace the degree requirement. - Minimum 2 years of experience in predictive analytics or data analysis, or an advanced degree (Master’s, PhD) in a quantitative field. - Proficient in training and validating analytical models including statistical and machine learning models. - Experience with one or more programming languages such as Python or R for statistical analysis and AI/ML modeling. - Capable of producing clear, well-documented code to ensure high levels of transparency. - Skilled in querying and handling data from both structured and unstructured databases using languages like SQL, HQL, or NoSQL. - Familiar with various data file formats including delimited numeric files, JSON/XML, and text or image files. - Knowledgeable in performing analytics utilizing descriptive, diagnostic, and inferential statistics. - Experienced with classical supervised modeling techniques such as regression and decision trees. - Familiarity with unsupervised modeling methods like clustering. - Effective communicator capable of presenting analytical findings to non-technical stakeholders.