Fraud & Risk Data Scientist - ML, Growth Analytics

Fraud & Risk Data Scientist - ML, Growth Analytics

Full-Time 50000 - 60000 Β£ / year (est.) No working from home possible
Transak

At a Glance

  • Tasks: Use ML models to tackle fraud and enhance user experience.
  • Company: Join Transak, a leading fintech company in Greater London.
  • Benefits: Full-time role with competitive salary and growth opportunities.
  • Other info: Collaborative environment focused on innovation and risk management.
  • Why this job: Make a real impact on product decisions while solving data challenges.
  • Qualifications: 2-5 years of experience with strong SQL and Python or R skills.

The predicted salary is between 50000 - 60000 Β£ per year.

Transak is hiring a mid-level Data Scientist in Greater London to join their Data team focused on Risk & Fraud. You'll reduce fraud while ensuring a smooth user experience through ML models and analytics. This role involves cross-functional collaboration to drive impactful product and policy decisions.

Candidates should have 2-5 years of experience, strong SQL skills, and solid Python or R knowledge. Experience in the fintech field is preferred. The position is full-time and offers a chance to work on significant data challenges.

Fraud & Risk Data Scientist - ML, Growth Analytics employer: Transak

Transak is an exceptional employer that champions innovation in the fintech space, particularly in risk management and fraud prevention. With a strong focus on employee growth, we offer a collaborative work culture where your contributions directly impact the onboarding experience for millions of users globally. Located at the forefront of blockchain technology, our team enjoys unique advantages such as access to cutting-edge tools and the opportunity to work alongside industry leaders like MetaMask and Coinbase.

Transak

Contact Details:

Transak Recruitment Team

We think you need these skills to ace Fraud & Risk Data Scientist - ML, Growth Analytics

Python
SQL
Problem-Solving Skills
Communication Skills
Automation
Attention to Detail
Data Engineering