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Open nowPosted 384 days ago

Associate Fraud Risk Data Scientist

sanrnd1 open role

Where
California, USA
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Your applicationOpen nowAssociate Fraud Risk Data Scientistsanrnd · California, USA

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12.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: posted 384 days ago

The posting

Position Title: Fraud Risk Data Scientist Location: Hybrid – San Jose, CA (Remote considered if no viable local candidates) Employment Type: Contract (1 year, potential extension based on business needs and performance) Work Schedule: Monday – Friday, Pacific Time

About the Role

We are seeking a talented and dedicated Fraud Risk Data Scientist to join our Risk Data & AI Innovation team. The ideal candidate will have a strong background in machine learning, data science, and analytics—specifically in risk and fraud detection. You will play a key role in designing, developing, and implementing AI and ML models to detect and mitigate fraud, while driving AI transformation within the risk management space.

Responsibilities

  • Design and develop machine learning and AI models to detect and mitigate fraud and risk.
  • Perform data analysis, statistical modeling, and model monitoring to ensure accuracy and efficiency.
  • Collaborate with cross-functional teams including product, engineering, and operations to deploy and refine models in real time.
  • Support stakeholders in effective model utilization and integration into business processes.
  • Develop dashboards and visualizations (e.g., Tableau, AWS Quicksight) to track key performance metrics.
  • Communicate analytical findings and model insights to technical and non-technical audiences, including executives.
  • Drive AI innovation within risk management activities, leveraging advanced data science and analytics.

Requirements

  • Experience: 2–6 years in machine learning/AI, data science, or risk analytics, ideally in industries such as eCommerce, online payments, user trust/risk/fraud, or investigation/product abuse.
  • Education: Bachelor’s or Master’s degree in Data Science, Data Analytics, Mathematics, Statistics, Data Mining, or related field (or equivalent practical experience).
  • Technical Skills: Strong proficiency in SQL and Python (including key data science libraries). Experience with AWS and data visualization tools such as Tableau or AWS Quicksight. Proficient in handling large datasets and performing complex data manipulations.
  • Analytical Skills: Ability to apply statistical and machine learning techniques to solve complex business problems.
  • Communication: Proven ability to clearly articulate technical results to both technical and business stakeholders.
  • Mindset: Comfortable with ambiguity, capable of turning unclear problems into measurable business outcomes.

Preferred Qualifications

  • Experience or aptitude in applying AI and data science solutions to risk and fraud problems.
  • Familiarity with AI tools such as LLMs (Large Language Models) for risk-related use cases.
  • Strong project management and stakeholder collaboration skills.
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