What are the responsibilities and job description for the Fraud Machine Learning Analyst position at Trivelta?
At Surt AI we make compliance simple, proactive and effective. Fraud signals are everywhere but spotting them before they become losses requires clarity and speed. Surt functions as a digital compliance officer for your business. It is trained to identify red flags, explain the risk in plain language and provide actionable insights you can trust.
Our platform transforms complex fraud patterns into a clear and digestible view. This allows you to focus on growth while knowing your compliance is protected. Surt AI is building the future of intelligent fraud detection and compliance for businesses of all sizes.
The Fraud Machine Learning Analyst will combine analytical skills and fraud detection knowledge to help perfect our machine learning engine which powers our identity verification platform, ensuring world-class security for our partners.
Responsibilities
Our platform transforms complex fraud patterns into a clear and digestible view. This allows you to focus on growth while knowing your compliance is protected. Surt AI is building the future of intelligent fraud detection and compliance for businesses of all sizes.
The Fraud Machine Learning Analyst will combine analytical skills and fraud detection knowledge to help perfect our machine learning engine which powers our identity verification platform, ensuring world-class security for our partners.
Responsibilities
- Serve as an advisor for product, engineering, and analytics teams, translating fraud analysis into best practices and procedural improvements.
- Collaborate on the development and deployment of fraud rule logic—leveraging analytics, experimentation, and feedback to drive ongoing improvements.
- Create and optimize fraud detection rules based on expert analysis of data and emerging fraud trends.
- Perform in-depth analyses of fraud patterns, operational data, and threat intelligence to uncover vulnerabilities, and present actionable insights to leadership and cross-functional teams.
- Monitor, document, and report on effectiveness of fraud prevention initiatives, sharing key metrics and trends across the business.
- Experience in Fraud, AML, Cybercrime, or Risk Management within tech, gaming, finance, or related sectors.
- Proven problem-solving and analytical abilities with a strong aptitude for pattern recognition, fraud trend analysis, and predictive modeling.
- Excellent communication and teamwork skills, with the ability to translate complex technical and analytical concepts for a broad audience.
- Bachelor’s degree in a quantitative field (e.g., Computer Science, Data Science, Statistics, Finance, Criminal Justice) or equivalent practical experience.
- Experience or interest in developing AI & graphs
- Certification in fraud analytics, AML, or risk management (e.g., CFE, CAMS) is a plus.
- Prior experience collaborating with product engineering teams to optimize rules based or machine learning models.