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6220 America Center Dr San Jose , CA 95002 US

Associate Fraud Risk Data Scientist

6220 America Center Dr San Jose , CA 95002 US

Posted: 10/29/2025 2025-10-29 2025-12-20 Employment Type: Contract Job Category: Database Management & Business Intelligence Job Number: 640113 Is job remote?: No

Job Description

Job Title: Associate Fraud Risk Data Scientist

Location: San Jose, CA

Contract length: 12 months

Schedule: Fulltime, M-F

Pay: up to $50/hr, DOE

Associate Fraud Risk Data Scientist Overview:

We are looking for a talented, enthusiastic and dedicated person to support the Fraud Risk Data Science Team within the Risk Data & AI Innovation Org. The incumbent will be responsible for supporting key projects associated with fraud detection, risk analysis and loss mitigation. This position requires a person who has experience with machine learning, model development with cutting edge AI/ML frameworks, performing analytics, statistical analysis and model monitoring. Experience with LLMs and other AI tools would be a big plus.

Associate Fraud Risk Data Scientist Qualifications:

Associate Fraud Risk Data Scientist Responsibilities:

Expected Outcomes for the Associate Fraud Risk Data Scientist:

Job Title: Associate Fraud Risk Data Scientist

Location: San Jose, CA

Contract length: 12 months

Schedule: Fulltime, M-F

Pay: up to $50/hr, DOE

Associate Fraud Risk Data Scientist Overview:

We are looking for a talented, enthusiastic and dedicated person to support the Fraud Risk Data Science Team within the Risk Data & AI Innovation Org. The incumbent will be responsible for supporting key projects associated with fraud detection, risk analysis and loss mitigation. This position requires a person who has experience with machine learning, model development with cutting edge AI/ML frameworks, performing analytics, statistical analysis and model monitoring. Experience with LLMs and other AI tools would be a big plus.

Associate Fraud Risk Data Scientist Qualifications:

  • 2-6 years of experience in machine learning/AI, data science, risk analytics & data analysis within relevant industry experience in eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse.
  • Bachelor’s/Master's degree in Data Science, Data Analytics, Mathematics, Statistics, Data Mining or related field or equivalent practical experience
  • Experience using statistics and data science (machine learning & AI) to solve complex business problems
  • Proficiency in SQL, Python, AWS, Excel including key data science libraries
  • Proficiency in data visualization including Tableau
  • Experience working with large datasets
  • Ability to clearly communicate complex results to technical experts, business partners, and executives including development of dashboards and visualizations, ie Tableau.
  • Comfortable with ambiguity and yet able to steer AI and machine learning projects toward clear business goals, testable hypotheses, and action-oriented outcomes
  • Demonstrated analytical thinking through data-driven decisions, as well as the technical know-how, and ability to work with your team to make a big impact.
  • Desirable to have experience or aptitude in solving problems related to risk using data science and analytics
  • Bonus: Experience with development and implementation of AI tools (e.g. LLMs) for risk use cases.

Associate Fraud Risk Data Scientist Responsibilities:

  • Design and develop machine learning and AI models to detect/mitigate fraud
  • Support stakeholders and cross-functional teams in effective usage of models
  • Drive AI transformation for all risk management activities
  • Work with product/engineering to implement, monitor and refine AI solutions and models

Expected Outcomes for the Associate Fraud Risk Data Scientist:

  • Work closely with team members and stakeholders to consult, design, develop, and manage fraud models and AI solutions.
  • Utilize data analysis to design and implement fraud models
  • Collaborate with cross-functional stakeholders including product managers and engineering teams to deploy data-driven fraud models and AI solutions that operate at scale and in real time for end customers.
  • Make business recommendations to leadership and cross-functional teams with effective presentations of findings at multiple levels of stakeholders.
  • Development of dashboard and visualizations to track KPI of fraud models implemented
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