Prompt Engineer
Alterya by Chainalysis is an AI-powered crypto fraud prevention tool designed to safeguard customers from authorized push-payment (APP) fraud and secure platforms with advanced threat intelligence.
Funding
Investors
Projects
About Alterya by Chainalysis
Alterya by Chainalysis connects crypto fraud across financial identifiers to block scams instantly. It safeguards customers from authorized push-payment (APP) fraud and secures platforms with AI-powered threat intelligence. The service detects and blocks fraudulent payments before funds leave a customer's account, monitors over $8B in monthly transactions, and protects over 100M users. It helps businesses grow by reducing false declines and increasing approval rates, thereby building customer trust and ensuring compliance with fraud management regulations. Alterya provides 360° protection from scams and money mules by automatically preventing payments to scammers, identifying fraudulent accounts during KYC processes, linking scam activity across networks with reliable intelligence, and tracking fraudulent activity on the platform.
Skills
About the Role
You will design and optimize prompts for LLM models to efficiently extract the data the team needs. You'll dig into questions to uncover deeper insights and better answers, constantly improving existing methods and challenging the status quo. You will build LLM prompts and data flows, research the web to define types of scams and scammers, analyze and monitor data pipelines using SQL, work with big data databases, and research customer and team requirements to create data-driven solutions that detect scammers effectively.
Requirements
- 2+ years' experience as a data analyst
- Excellent analytical skills
- Strong SQL skills with experience querying large, complex data sets
- Experience with Python data functions
- Fluent English (written & verbal)
- Good interpersonal communication skills
- Quick grasp of new data and data systems
Responsibilities
- Build LLM prompts and data flows
- Research the web to find and define types of scams and scammers
- Analyze and monitor data pipelines using SQL
- Work with big data databases
- Research customer and team requirements
- Analyze fraudulent and scam activity online
- Create data-driven solutions to detect scammers effectively