Associate Fraud Risk Data Scientist
Community Talent Partners · San Jose, CA, US
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- Location
- San Jose, CA, US
- Posted
Location: San Jose, CA (Hybrid)
Experience Level: Mid–Senior
Experience Required: 2–6 Years
Education Required: Bachelor’s Degree in Data Science, Mathematics, Statistics, Analytics, or related field
Job Function: Finance / Data Science
Industry: Financial Services
Positions Available: 1
Relocation Assistance: No
Visa Sponsorship Eligibility: No
About the Role
Community Talent Partners is seeking an Associate Fraud Risk Data Scientist for a hybrid opportunity based in San Jose, CA. The ideal candidate will have hands-on experience using SQL, Python, Tableau, and AWS to build and deploy data-driven fraud detection and risk analytics models in eCommerce, online payments, or fintech environments.
This role is ideal for data science professionals passionate about applying machine learning and AI to identify, prevent, and mitigate fraud while driving trust and safety at scale.
Key Responsibilities
- Design, develop, and deploy fraud detection and risk mitigation models using machine learning and AI.
- Use SQL and Python to analyze large datasets, detect fraud patterns, and develop predictive insights.
- Build dashboards and visualizations in Tableau to monitor model performance and KPIs.
- Work with product and engineering teams to implement scalable fraud solutions in AWS environments.
- Communicate analytical findings and recommendations to business and technical stakeholders.
Must-Have Qualifications
- 2–6 years of experience in fraud risk analytics, machine learning, or data science , preferably in eCommerce, online payments, or fintech.
- Proven expertise in SQL and Python for data analysis and model development.
- Strong understanding of fraud detection , risk analytics , and data-driven decision-making.
- Proficiency in Tableau (or equivalent) for data visualization.
- Experience working in AWS or similar cloud environments.
- Bachelor’s degree in Data Science, Statistics, Mathematics, Analytics, or a related quantitative field.
Nice to Have
- Experience developing AI tools or LLMs for fraud or risk use cases.
- Knowledge of risk modeling in large-scale financial or eCommerce systems.
- Ability to explain complex technical findings to non-technical stakeholders.
Additional Details
- Hybrid role (onsite in San Jose preferred; remote considered if local candidates unavailable).
- Contract-based position (approximately one year; may extend based on performance).
- Schedule: Monday–Friday, Pacific Time.
- Interview Process: 2–3 virtual interviews, including a SQL proficiency assessment.
If you have strong technical skills in SQL, Python, Tableau, AWS , and hands-on experience combating fraud in digital or financial systems , we encourage you to apply today.
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