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
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