Senior Data Scientist β€” Fraud & Risk ML, Stock Options in London

Senior Data Scientist β€” Fraud & Risk ML, Stock Options in London

London Full-Time 60000 - 75000 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Create ML models to combat fraud and enhance financial decision-making.
  • Company: Join a fast-growing fintech platform focused on innovation.
  • Benefits: Stock options, competitive salary, and opportunities for professional growth.
  • Other info: Collaborative environment with a focus on transforming ideas into reality.
  • Why this job: Make a real impact by solving complex financial challenges with data.
  • Qualifications: Experience in data science and machine learning is essential.

The predicted salary is between 60000 - 75000 Β£ per year.

ARQ is seeking a Senior Data Scientist to build the intelligence layer behind its financial products.

You will develop ML models to detect fraud, prevent losses, and scale decisions across millions of customers.

You will move problems from idea to production in partnership with Product, Engineering, and Operations teams.

You will work on risk and financial crime challenges, transform business problems into data-driven solutions, and influence customer outcomes at ARQ’s growing fintech platform.

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Senior Data Scientist β€” Fraud & Risk ML, Stock Options in London employer: ARQ

ARQ is an exceptional employer that fosters a dynamic and inclusive work culture in the heart of London, where innovation meets opportunity. Employees benefit from competitive salaries, stock options, and a clear pathway for professional growth, all while contributing to a mission that aims to transform global financial interactions. Join us to be part of a forward-thinking team that values your contributions and supports your career aspirations.

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Contact Details:

ARQ Recruitment Team

We think you need these skills to ace Senior Data Scientist β€” Fraud & Risk ML, Stock Options in London

Machine Learning
Fraud Detection
Risk Analysis
Data-Driven Solutions
Collaboration with Product Teams
Collaboration with Engineering Teams
Collaboration with Operations Teams