Lead Data Scientist: Scams Prevention & Risk Insights

Wise; Greater London; On-site; GBP 110,000 - 170,000; Full time

Job summary

Wise is seeking a Lead Data Scientist to join our growing Scams Prevention team. This role is a unique opportunity to work behind the scenes of company transactions, understand how we mitigate risk, and provide customers with seamless service.

You will build models to detect fraud, protect accounts, and collaborate across engineering, product, and security. Your work will drive safer experiences for millions of Wise users worldwide.

Qualifications

• Experience in fraud detection, cybersecurity, or fintech.
• Built ML models for Send Scam (Victim Identification) and Account Takeover.
• Proficient in Python, R, or similar.
• Experience with Hadoop, Spark, SQL.
• Familiar with anomaly detection, supervised/unsupervised learning, deep learning and graph methods.
• Able to communicate complex concepts to non-technical stakeholders.
• Proactive problem-solver focused on protecting users.

Responsibilities

• Lead the development and deployment of advanced ML models to detect, predict, and mitigate account takeover attempts.
• Analyse large volumes of data to identify trends, patterns, and anomalies related to ATO and Send Scam.
• Design experiments to evaluate fraud detection systems and improve performance.
• Collaborate with security analysts and engineers to translate requirements into data insights and solutions.
• Develop data pipelines, algorithms, and tools for real-time detection and response to fraud.
• Stay updated on ML and fraud prevention techniques to maintain state-of-the-art capabilities.
• Mentor junior data scientists and foster collaboration within the team.

Skills

Data science

Fraud detection

Cybersecurity

Fintech

Python

R

Big data

Cross-functional

Tools

Hadoop

Spark

SQL

Git

Java

Job description

Wise is seeking a Lead Data Scientist to join our growing Scams Prevention team. This role is a unique opportunity to work behind the scenes of company transactions, understand how we mitigate risk, and provide customers with seamless service.

You will build models to detect fraud, protect accounts, and collaborate across engineering, product, and security. Your work will drive safer experiences for millions of Wise users worldwide.