Associate Fraud Strategy Data Scientist (Hybrid)

Job Description

Associate Fraud Strategy Data Scientist

San Jose, CA (Hybrid) | Contract | $50 / hour

Duration : 1-year contract (to cover multiple leaves), with possible extension based on performance

Analyze fraud patterns, build predictive models, and drive risk mitigation strategies at a fast-paced fintech consultancy

A leading consultancy firm supporting a fast-growing fintech client is hiring a contract Associate Fraud Strategy Data Scientist to help fight fraud at scale. This is a hybrid role based in the San Jose area, ideal for a mid-level data scientist with experience in fraud, payments, or eCommerce.

The ideal candidate is a curious, impact-driven professional who can dive into large datasets, design fraud detection strategies, and clearly communicate data-driven insights to technical and non-technical teams.

Position Overview

In this role, you’ll partner with the Fraud Risk Strategy team to design and refine fraud detection rules, support strategy development with data science models, and surface actionable insights using SQL, Python, Tableau, and large-scale datasets. You’ll also work cross-functionally with product and engineering to improve fraud mitigation capabilities and customer experience.

Key Responsibilities

Design fraud detection and mitigation rules

Build Python scripts and data science models to support risk strategies

Analyze large datasets to identify fraud patterns and root causes

Collaborate with engineering and product teams to strengthen fraud controls

Develop dashboards and data visualizations using Tableau

Guide execution of fraud strategy roadmaps

Present findings and recommendations to leadership and cross-functional stakeholders

Requirements

Required Qualifications

Bachelor's degree in Data Analytics, Data Science, Statistics, Mathematics, or related field

2 years max of professional experience in risk analytics, fraud detection, or online payments

Advanced SQL skills and proficiency in Python (plus data science libraries)

Strong experience with Tableau or similar data visualization tools

Experience working with large datasets and deriving actionable insights

Ability to communicate findings clearly across stakeholders and teams

Preferred Skills & Bonus Experience

AWS, Quicksight, or cloud-based analytics platforms

Experience working with fraud rule systems or ML models

Understanding of fraud typologies or abuse detection

Experience supporting investigations or product abuse cases

Prior exposure to eCommerce, fintech, or online marketplaces

Expected Outcomes (6–12 Months)

Collaborate on new fraud strategies based on emerging threats

Deliver dashboards tracking KPIs and fraud loss metrics

Deploy data-backed solutions that improve fraud controls while enhancing customer experience

Support risk mitigation efforts that reduce financial losses across the platform

Requirements

2 years max of professional experience in risk analytics, fraud detection, or online payments Advanced SQL skills and proficiency in Python (plus data science libraries) Strong experience with Tableau or similar data visualization tools Experience working with large datasets and deriving actionable insights Ability to communicate findings clearly across stakeholders and teams