- Company Name
- USAA
- Job Title
- Data Scientist II - Fraud
- Job Description
-
**Job Title**
Data Scientist II – Fraud
**Role Summary**
Develop, refine, and deploy advanced predictive models to detect and prevent fraud across credit card, debit card, check, deposit, digital payments, claims, and disputes. Drive innovation in modeling techniques, collaborate with cross‑functional teams, and maintain model risk and governance standards.
**Expectations**
- Deliver high‑impact fraud detection models that reduce losses and improve member experience.
- Continuously update models to adapt to evolving fraud tactics.
- Communicate model outcomes to technical and non‑technical stakeholders.
- Ensure models meet Model Development Control (MDC) and Model Risk Management (MRM) compliance.
**Key Responsibilities**
- Capture, clean, and analyze structured and unstructured data.
- Select and apply appropriate statistical, machine‑learning, or AI techniques.
- Build, validate, and score models; integrate them into production pipelines.
- Write clear, well‑commented code and technical documentation.
- Collaborate with Data Engineering, IT, and business teams to deploy solutions.
- Monitor model performance, assess risk, and recommend enhancements.
- Stay current with new analytics methods, tools, and best practices.
**Required Skills**
- Proficiency in Python or R for statistical analysis and model development.
- Strong coding practices: readable, commented, and maintainable.
- SQL/HQL/NoSQL querying and data preprocessing from structured/semi‑structured sources.
- Experience with supervised learning (logistic regression, decision trees, random forests, SVM, etc.) and unsupervised techniques (k‑means, hierarchical clustering, DBSCAN, etc.).
- Knowledge of descriptive, diagnostic, and inferential statistics for ad‑hoc analytics.
- Ability to translate business questions into analytical problems and present results clearly.
**Required Education & Certifications**
- Bachelor’s degree in mathematics, computer science, statistics, economics, finance, actuarial science, engineering, or a related quantitative field **or** equivalent experience.
- Minimum 2 years of predictive analytics or data analysis experience **or** an advanced degree (Master’s, PhD) in a quantitative discipline.
- Demonstrated experience in training, validating, and deploying statistical, machine‑learning, or advanced analytics models.
San antonio, United states
On site
Junior
17-12-2025