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Data Scientist

Posted 4 days ago

  • London, Greater London
  • Any
  • External
  • Expires In 3 months
Product Data ScientistAre you ready to combat fraud and revolutionise the payments industry? Our client, a pioneering FinTech startup, is on a mission to eliminate payments scams and build the next generation of tools to combat consumer fraud.Company Profile:We’re working with a super early-stage B2B FinTech that recently closed a seed funding round, and is now focused on building out a team to tackle the biggest challenges in payments fraud. The team is small, dynamic, and passionate about creating unprecedented transparency and control in payment transactions. The Opportunity:As a Product Data Scientist, you will be at the forefront of developing innovative solutions to combat fraud in the payments sector. You will support product development with robust data analytics and provide subject matter expertise in payments and fraud detection. This is a unique opportunity to join an ambitious fin-tech company as they embark on their scaling journey, and a chance to play an integral role in shaping the company’s products.Responsibilities:Design and implement advanced fraud detection models and algorithms to identify and mitigate APP fraud.Provide subject matter expertise in payments, fraud, and risk management to inform product strategy and development.Analyse large datasets to uncover patterns, trends, and insights related to fraudulent activities.Collaborate with the product team to develop and refine fraud prevention tools and features.Continuously evaluate and improve the accuracy and effectiveness of fraud detection systems.Develop and maintain transaction monitoring systems and risk scoring models.Communicate complex data insights to senior stakeholders in a clear and actionable manner.Requirements:3+ years of experience in data science, ideally with a focus on fraud detection, payments, credit, or a related field.Proficiency in PythonFamiliarity with payment systems, transaction monitoring, fraud models, and risk scoring analysis. Software & Data Engineering experience is a plus (Java, Rust)Industry experience in credit, actuarial, or payment sectors is a plus.
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