Associate Fraud Risk Data Scientist

ZipRecruiter; San Jose (CA); Hybrid; USD 125,000 - 150,000; Part time

Job summary

A leading recruitment platform is seeking an Associate Fraud Risk Data Scientist in San Jose, CA (Hybrid). The role involves developing AI models for fraud detection and risk analysis, requiring 2–6 years in data science and strong proficiency in SQL and Python. Ideal candidates will have a Bachelor's degree and be adept at statistical analysis. This is a contract position with a pay rate of $50/hour.

Qualifications

• 2–6 years in machine learning/AI, data science, risk analytics, or fraud analytics.
• Hands-on experience with large datasets and statistical analysis for fraud mitigation.
• Proven background in eCommerce, online payments, trust & safety, or product abuse domains.

Responsibilities

• Design and develop machine learning and AI models to detect and mitigate fraud.
• Collaborate with product and engineering teams to implement, monitor, and refine models.
• Present analytical findings and business recommendations to leadership.

Skills

Machine Learning & Artificial Intelligence model development

Data Science & Risk Analytics

Dashboard creation and KPI tracking

Model monitoring and performance optimization

Excellent communication and presentation skills

Education

Bachelor’s Degree

Master’s Degree

Tools

SQL

Python

AWS

Tableau

Excel

Job description

Overview

Associate Fraud Risk Data Scientist — Location: San Jose, CA (Hybrid); Pay Rate: $50/hour; Employment Type: Contract (1 Year – Possible Extension); Experience Level: Mid–Senior (5 Years); Education: Bachelor’s Degree (Master’s); Visa: GC and USC only

About the Role

We are seeking a talented and dedicated Associate Fraud Risk Data Scientist to join the Fraud Risk Data Science Team within the Risk Data & AI Innovation Organization. You will work on key projects involving fraud detection, risk analysis, and loss mitigation, applying machine learning, AI, and data analytics to tackle complex business challenges.

The ideal candidate has hands-on experience in data science, fraud risk analytics, and AI model development within eCommerce, online payments, or product abuse/investigation environments.

Key Responsibilities

• Design and develop machine learning and AI models to detect and mitigate fraud.
• Collaborate with product and engineering teams to implement, monitor, and refine models.
• Support stakeholders and cross-functional teams in effective usage of models and analytics.
• Leverage data analysis and visualization tools (Tableau, AWS QuickSight) to develop dashboards and KPIs.
• Present analytical findings and business recommendations to leadership and technical partners.
• Drive AI transformation across risk management initiatives.

Desired Skills & Qualifications

Experience:

• 2–6 years in machine learning/AI, data science, risk analytics, or fraud analytics.
• Hands-on experience with large datasets and statistical analysis for fraud mitigation.
• Proven background in eCommerce, online payments, trust & safety, or product abuse domains.

Technical Proficiency:

• SQL (strong proficiency required)
• Python (data science libraries such as pandas, NumPy, scikit-learn, TensorFlow, etc.)
• AWS (including AWS QuickSight)
• Tableau for advanced data visualization
• Excel and statistical modeling tools

Skills:

• Machine Learning & Artificial Intelligence model development
• Data Science & Risk Analytics
• Dashboard creation and KPI tracking
• Model monitoring and performance optimization
• Experience with LLMs or AI-based fraud risk tools (bonus)
• Excellent communication and presentation skills

Expected Outcomes

• Develop and maintain fraud detection and risk mitigation models.
• Deploy data-driven AI solutions that operate in real-time for end customers.
• Create dashboards and visual reports for continuous model performance tracking.
• Partner cross-functionally to improve risk intelligence and fraud prevention strategies.

Additional Details

• Schedule: Monday–Friday, Pacific Time (Day Shift)
• Interviews: 2–3 Zoom rounds, including a SQL assessment in the first interview.
• Hybrid Role: Candidates must be based in or near San Jose, CA
• Duration: 1-year contract