Associate Fraud Strategy Data Scientist

Job Title:

Data Professional Location:

Onsite San Jose CA Salary Range:

$50 w2…. w2 only Introduction We are seeking a talented and dedicated Data Professional to support the Fraud Risk Strategy team. This role focuses on fraud detection, risk analysis, and loss mitigation by leveraging advanced analytics, predictive modeling, and visualization tools. The ideal candidate combines strong technical skills with business acumen to deliver actionable insights and strategies that protect both the company and its customers. Required Skills & Qualifications Maximum

2 years of experience

in risk analytics, data analysis, or data science

Bachelor’s degree in

Data Analytics, Data Science, Mathematics, Statistics, Data Mining

or related field (or equivalent experience)

Proficiency in

SQL, Python, and Excel

(including key data science libraries)

Experience with

data visualization

using Tableau and/or AWS QuickSight

Ability to analyze

large datasets

to drive actionable insights

Strong knowledge of

statistics and data science applications

for business problems

Clear communication skills, including the ability to present complex findings to both technical and business audiences

Comfortable managing

ambiguity

while driving toward business outcomes

Preferred Skills & Qualifications Experience with

data models and rule development

Knowledge of

project management practices

Familiarity with fraud investigations, fraud typologies, and payment rule systems

Experience collaborating with

machine learning teams

Day-to-Day Responsibilities Design and implement

fraud detection and mitigation rules

Develop

Python scripts and predictive models

to support fraud strategies

Investigate fraud cases, perform root cause analysis, and recommend solutions

Set and refine

risk strategies

for various fraud types

Partner with product and engineering teams to

improve fraud control capabilities

Build and present dashboards and visualizations to track

fraud KPIs

Provide actionable recommendations to stakeholders at multiple levels

Expected Outcomes (6–12 Months) Collaborate with stakeholders to design and manage fraud strategies and rules addressing emerging fraud trends

Utilize analytics to create

real-time, scalable fraud solutions

that balance risk mitigation with customer experience

Deliver business recommendations through effective presentations and reporting to leadership and cross-functional teams

Develop dashboards and visualization tools to track

key performance indicators (KPIs)

for fraud strategies

Benefits & Culture We are committed to building a collaborative, innovative environment where data-driven decisions and fraud prevention strategies create measurable impact. TECH #Onsite #J-18808-Ljbffr