Data Scientist - Fraud Analysis

- Bachelor’s degree in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or related quantitative field; or 4 years of experience in a similar role may substitute for degree. - Minimum of 2 years experience in predictive analytics or data analysis or an advanced degree (e.g., Master’s, PhD) in a relevant field. - Proficient in training and validating statistical, physical, machine learning, and advanced analytics models. - Skilled in at least one multifaceted scripting language (e.g., Python, R) for statistical analysis and AI/ML model development. - Capability to write clear, detailed, and transparently commented code. - Experienced in querying and preprocessing data from structured and unstructured databases using languages like SQL, HQL, or NoSQL. - Familiarity with handling structured, semi-structured, and unstructured data files such as numeric data, JSON/XML, and others. - Knowledgeable in conducting ad-hoc analytics using descriptive, diagnostic, and inferential statistics. - Understanding of classical supervised modeling techniques like linear/logistic regression, decision trees, etc. - Exposure to unsupervised modeling concepts such as k-means clustering and DBSCAN. - Strong communication skills to convey analytical results to non-technical stakeholders.