ZipRecruiter
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
#J-18808-Ljbffr
— 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
#J-18808-Ljbffr