Team Lead, Senior Risk Analyst (Anti-Fraud) at Binance
Wellington City, Wellington, New Zealand -
Full Time


Start Date

Immediate

Expiry Date

22 Jul, 25

Salary

0.0

Posted On

23 Apr, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Payments, Fintech, Python, Financial Services, Sql, Cryptocurrency, Communication Skills

Industry

Financial Services

Description

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by over 250 million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.

REQUIREMENTS:

  • At least 5 years of relevant experience in risk control or a related field.
  • Background in cryptocurrency, banking, financial services, payments, fintech, or similar industries.
  • Demonstrates a strong commitment and determination to protect legitimate users from fraudulent activity.
  • Proven ability to lead and motivate a team towards shared goals.
  • Strong investigative mindset with well-developed data analysis capabilities.
  • Proficient in Python and SQL.
  • Outstanding interpersonal and communication skills.
  • Familiarity with blockchain analysis tools is a plus, though not essential.
  • Comfortable collaborating within a diverse, international team of highly skilled professionals.
Responsibilities
  • Supervise a team of 4–5 analysts in detecting, monitoring, and analysing fraud-related activities.
  • Lead comprehensive investigations into anomalous transactions and user behaviours to identify fraudulent patterns.
  • Carry out feature extraction and data analysis to uncover key fraud indicators and improve detection models.
  • Devise and implement strategic risk mitigation plans to proactively manage emerging threats.
  • Design and refine alert mechanisms and victim support initiatives to reduce the impact of fraud.
  • Collaborate with cross-functional teams, including Engineering, Technology, Customer Support, and Legal, to enhance fraud prevention and safeguard users.
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