Senior Risk Data Analyst - Fincrime Fraud Monitoring
Senior Risk Data Analyst - Fincrime Fraud Monitoring
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Job Description
The Team
The Customer Risk Monitoring team is responsible for implementing and maintaining the analytical intelligence that protects Teya and its customers from financial risks including fraud money laundering and terrorism financing. Our goal is to minimise financial losses and risk exposure while supporting and maintaining our customers trust and ensuring compliance with regulatory requirements.
We work closely with the Operations team to investigate suspicious activities and collaborate crossfunctionally with Compliance Risk Platform Engineering and product leaders to build and continuously improve the intelligence powering our detection and monitoring systems.
The role
As a Data Analyst in the Customer Risk Monitoring team you will:
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 datainformed 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 coursecorrect with confidence
Promote a culture of datadriven decisionmaking across the organisation
Qualifications :
Were looking for a Senior Data Analyst with a strong analytical foundation and a passion for tackling complex ambiguous problems in the financial risk domain.
Musthaves
4 years of professional experience as a data analyst preferably in fraud AML or financial risk monitoring
Solid understanding of statistical concepts and experience applying methods such as forecasting time series analysis A/B testing or regression analysis
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
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 nontechnical stakeholders
Experience working collaboratively with crossfunctional partners including Operations Compliance Engineering and Product
Selfstarter who thrives in a fastpaced highambiguity environment and takes ownership of their work from start to finish
Nicetohaves
Experience in acquiring services or the payments industry
Bachelors or Masters degree in a quantitative discipline (e.g. Mathematics Statistics Computer Science Economics)
Direct experience with problems such as AML scenario tuning fraud rule optimisation or detection intelligence design
Familiarity with regulatory or compliancedriven analytics environments
Fincrime certifications such as CAMS ICA or equivalent
Additional Information :
The Perks
Competitive salary;
Health Insurance;
25 days of Annual leave Bank holidays);
Flexible working hours as long it suits both you and your team.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
