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Associate Fraud Risk Data Scientist

Macpower Digital Assets Edge LLC
San Jose, CA, United States
3 days ago
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Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Working hours
Regular working hours
Job source
www.thejobnetwork.com

Tech stack

Microsoft Excel Artificial Intelligence Amazon Web Services Data Analysis Big Data Data Mining Data Visualization Fraud Prevention and Detection Python (Programming Language) Machine Learning Payment Gateway Raw Data
+3 more
SQL Databases Tableau (Software) Large Language Models

Job description

  • Our client is seeking a talented, enthusiastic, and dedicated professional to join their Fraud Risk Data Science Team within our Risk Data & AI Innovation Organization. The incumbent will drive critical projects focused on fraud detection, risk analysis, and loss mitigation. We seek a strategic-minded data scientist who can make substantial, actionable impacts using AI and analytics to drive fraud risk management excellence.

Requirements

  • The ideal candidate will have 2-6 years of experience in machine learning, AI, data science, and risk analytics, with a strong background in eCommerce, online payments, user trust, risk, fraud, or product abuse investigations. They will hold a Bachelor’s or Master’s degree in Data Science, Analytics, Mathematics, Statistics, Data Mining, or a related field, or possess equivalent practical experience.
  • The role demands expertise in statistics and data science methods to solve complex business challenges. Proficiency in SQL, Python, AWS, Excel, and key data science libraries is essential. Candidates must also demonstrate strong skills in data visualization, particularly Tableau, and be comfortable working with large datasets. Experience with LLMs and AI tools for risk use cases is considered a valuable asset.
  • Responsibilities include designing, developing, and implementing machine learning and AI models to detect and mitigate fraud. The Associate will collaborate with stakeholders and cross-functional teams to deploy scalable, real-time fraud solutions. They will monitor model performance, refine AI tools, and support AI transformation initiatives within risk management.
  • The candidate will also be responsible for creating dashboards and visualizations to track key performance indicators, clearly communicating complex analytical insights to technical experts and business leaders alike. Comfort with ambiguity and a results-driven approach to data science projects are key to success.
  • This hybrid role is based in the San Jose area, with remote consideration if local candidates are unavailable. It is a contract position covering multiple leaves over one year, with potential for extension based on business needs and performance. Work hours are Monday to Friday, Pacific Time.
  • Candidates will undergo multiple Zoom interviews, including an SQL assessment in the first round. Strong SQL proficiency and prior experience applying data science to fraud mitigation remain critical selection criteria.

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