Are you an experienced Data Analyst looking to expand your skillset in the exciting space of fraud detection?
What’s the Job?
As a Data Analyst, you will be using your knowledge of fraud while matching it with your statistical and analytical skills to work alongside our top tier clients in the full implementation of our specialized real-time platform. You will report directly to our VP of Professional Services, and will have the opportunity to collaborate with other Data Analysts across our various offices both domestic and international.
We are looking for somebody who is able to speak Spanish or Portuguese as we continue expanding into Latin America. This is a requirement for this role.
You’ll have an opportunity analyze billions of transactions from our vast client base of Fortune 500 companies, looking for suspicious activity in order to detect issues and trends. Ultimately, your work will have a major impact on our company’s success.
Who are we?
We are a specialized platform that provides fraud analytics and digital identity solutions for companies of all sizes. As a data-driven organization that prides itself on its cutting-edge technology and expertise of its employees, we provide a valuable service to our clients in an ever-changing world of increased concerns over cyber-crime and fraud.
What Skills Do We Need?
- Advanced knowledge of SQL and data analytics
- Domain experience in fraud detection is critical
- Intermediate to advanced in Spanish or Portuguese
- Strong customer facing skillset, including top level communication and presentation skills
- $70,000 – $90,000 plus competitive bonus
- Full Benefits (medical, dental, vision)
- Retirement/401(k) Plan
- Generous Paid Time Off (PTO) Policy
- Great work / life balance
What’s In It For You?
This is a great opportunity for an experienced fraud data analyst to join one of the most exciting and cutting-edge startups in New York. You will work in our brand-new office in the Empire State building, with incredible south facing views of all of downtown Manhattan!