Senior Fraud Risk Data Modeler - Remote

Hidden Jobs; United States; Remote; USD 83,000 - 143,000; Full time

Benefits offered by this job

15 days flexible time off

Job summary

Hidden Jobs is seeking a senior-level data modeling professional to support fraud risk detection within our analytics function. The role emphasizes designing, validating, and maintaining models to surface suspicious activity.

It is remote within the United States, with San Diego, CA listed as the reference office, and requires a full-time day-shift schedule. Responsibilities include building models, applying quantitative methods, documenting approaches, and collaborating with analytics, risk,

Qualifications

• Senior-level experience in data modeling or analytics.
• Hands-on background with fraud, risk, or anomaly detection in financial services.
• Strong proficiency in SQL and statistical or machine-learning techniques.
• Ability to communicate methodology and results to technical and non-technical audiences.

Responsibilities

• Design, build, and refine data models for fraud risk detection across financial services datasets.
• Apply quantitative methods to identify patterns of fraudulent or high-risk behavior.
• Document modeling approaches, inputs, and performance for downstream consumers.
• Collaborate with analytics, risk, and engineering to translate model outputs into workflows.
• Monitor deployed models for stability and accuracy as new data and fraud patterns emerge.

Skills

SQL

Statistical Methods

Data Modeling

Senior Experience

Job description

Hidden Jobs is seeking a senior-level data modeling professional to support fraud risk detection within our analytics function. The role emphasizes designing, validating, and maintaining models to surface suspicious activity.

It is remote within the United States, with San Diego, CA listed as the reference office, and requires a full-time day-shift schedule. Responsibilities include building models, applying quantitative methods, documenting approaches, and collaborating with analytics, risk,