Associate Fraud Strategy Data Scientist

Job Description

Job Description

Associate Fraud Strategy Data Scientist (Hybrid | San Jose, CA)

(12-Month Contract | Potential to Extend | U.S. Citizens or Authorized Workers Only)

Job Overview

We're seeking a highly analytical and motivated Associate Fraud Strategy Data Scientist to join a leading fintech organization's Fraud Risk Strategy team.

This role is perfect for an early-career data professional (02 years of experience) who's ready to apply data science and analytics to solve real-world fraud and risk challenges in eCommerce, online payments, and digital transactions.

Youll support the design, testing, and optimization of fraud detection models and rules, working closely with product and engineering partners to enhance user trust, reduce losses, and protect our customers.

Key Responsibilities

Analyze and model large, complex datasets to detect, prevent, and mitigate fraud across multiple digital channels.

Apply s tatistical and machine-learning techniques (regression, classification, feature engineering, clustering) to identify fraudulent patterns and emerging risks.

Develop and maintain SQL-based datasets, dashboards, and visualizations to monitor key performance indicators and strategy outcomes.

Partner with senior data scientists, analysts, and risk strategists to implement and evaluate fraud detection models.

Communicate analytical findings, insights, and recommendations clearly to technical and business stakeholders.

Use Tableau or AWS Quicksight to design visual dashboards that support fraud strategy decisions.

Conduct ad-hoc investigations and reporting to support ongoing fraud prevention initiatives.

Required Qualifications

Experience :

Maximum of 2 years in risk analytics, data analysis, or data science , ideally within eCommerce, online payments, user trust / risk / fraud, or product-abuse investigations.

Education :

Bachelor's degree in Data Science, Data Analytics, Mathematics, Statistics, Data Mining, or a related quantitative field; or equivalent hands-on experience.

Technical Skills :

Strong SQL proficiency for querying and manipulating large datasets.

Hands-on Python experience with data-science libraries (NumPy, Pandas, Scikit-learn, etc.).

Proficiency with Excel for exploratory and statistical analysis.

Demonstrated experience applying statistics and data science to solve complex business problems, preferably related to fraud detection or risk mitigation.

Experience creating data visualizations and dashboards using Tableau or AWS Quicksight.

Comfortable working with large-scale datasets in cloud or enterprise environments.

Preferred Skills

Familiarity with f raud typologies, payments data, or rule-based detection systems.

Understanding of data pipelines (ETL), predictive modeling, and A / B testing.

Excellent written and verbal communication skills with an ability to translate analytics into actionable business insights.

Position Details

Type : 12-Month Contract (covering multiple employee leaves)

Schedule : Monday - Friday | Day Shift

Location : Hybrid San Jose, CA (local candidates only)

Relocation Assistance : Not provided

Why Join

This role offers the opportunity to :

Gain hands-on experience with fraud analytics and risk modeling at scale.

Work alongside top data scientists and fraud strategists, shaping digital trust and security.

Develop advanced technical and analytical skills in a collaborative, growth-oriented environment.