Hybrid Risk Data Analyst – Fincrime & Fraud Monitoring

Posted 2 months ago

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About the role

  • Risk Data Analyst at Teya, focusing on fraud detection and financial crime monitoring. Collaborating with cross-functional teams to enhance analytical intelligence and drive data-informed decisions.

Responsibilities

  • Develop and refine the intelligence used to detect financial crime, balancing efficacy with operational efficiency to reduce false positives, investigation time, and customer friction
  • Deliver actionable insights that directly improve detection rates, uncover new risk patterns, and inform prevention strategies
  • Act as a bridge between data and the business, collaborating closely with Operations, Compliance, Engineering, and Product teams to shape and prioritise analytical initiatives
  • Identify opportunities to improve and automate monitoring, escalate emerging threats, and continuously evolve our understanding of risk
  • Build and maintain clear and impactful dashboards, reports, and documentation to monitor key metrics, surface relevant trends, and drive data-informed decisions
  • Partner with data engineering to design and maintain scalable, reliable data models and ETLs that underpin both operational and strategic use cases
  • Help define and analyse fraud and AML KPIs, helping the business plan and course-correct with confidence
  • Promote a culture of data-driven decision-making across the organisation

Requirements

  • A minimum of two years of professional experience as a data analyst, working in financial crime and/or transaction monitoring
  • Direct experience with problems such as AML scenario tuning, fraud rule optimisation, or the design of detection intelligence is strongly preferred.
  • Experience in producing insights that led to measurable improvements, ideally in relevant domains such as fraud, AML detection, or operations
  • Advanced proficiency in SQL and experience working with large, complex, and sometimes messy datasets
  • Experience designing, building, and maintaining ETL pipelines or data models, ideally using tools like dbt
  • Proficient in Tableau or equivalent BI tool
  • Proficiency in Python for data analysis, including data manipulation, visualisation, and basic modelling
  • Strong data storytelling and communication skills: you can translate complex data into clear, actionable recommendations for both technical and non-technical stakeholders
  • Experience working collaboratively with cross-functional partners, including Operations, Compliance, Engineering and Product
  • Self-starter who thrives in a fast-paced, high-ambiguity environment and takes ownership of their work from start to finish

Benefits

  • Health Insurance
  • Meal Allowance
  • 25 days of Annual leave (+ Bank holidays)
  • Public Transportation Card
  • Frequent team events & activities in the office and outside
  • Office snacks every day
  • Friendly, comfortable and informal office environment

Job title

Risk Data Analyst – Fincrime & Fraud Monitoring

Job type

Experience level

JuniorMid level

Salary

Not specified

Degree requirement

Bachelor's Degree

Location requirements

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