Senior Data Analyst - Fraud Prevention
Senior Data Analyst - Fraud Prevention
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Job Description
Become a part of our story:
Were looking for exceptional talent to join our mission. We offer a chance to create impact in a highenergy and connected culture while benefiting from continuous learning opportunities a supportive community which is proud to serve our mission and comprehensive benefits.
The Team:
The Customer Risk Monitoring team part of the Acceptance group is responsible for implementing and maintaining the analytical intelligence that protects Teya and its customers from exposure to financial risks including fraud and money laundering. Our goals are to minimise financial losses to Teya while maintaining customer trust and ensuring compliance with regulatory requirements. This team aligns very closely with the Ops teams investigating suspicious activities.
As a senior data analyst in fraud you will work collaboratively with the data scientists building our inhouse fraud intelligence the engineers integrating it the Ops investigators using this intelligence in the real world and the team leadership aligning this work with roadmap goals and strategic planning. A key expectation for this role is to help shape the short medium and longterm direction of fraud detection automated intervention and risk monitoring at Teya and we expect the ideal candidate to understand and be excited about this opportunity.
The Role:
As a Senior Data Analyst in fraud you will:
Deliver insights that lead to actionable and measurable outcomes such as improvement in the fraud detection rate reduction in false positive rate and decreased time to detect and investigate fraudulent activity
Be a key individual contributor to a diverse and innovative team developing a deep understanding of data inputs and driving continuous improvement while addressing fastmoving risks and opportunities.
Work with senior product business and engineering leaders to analyse data identify opportunities for building new models develop and maintain realtime dashboards and deliver insights through indepth reports
Effectively manage business stakeholders and drive initiatives to promote actionable insights identifying and prioritising requirements and owning a roadmap of deliverables
Build and maintain dashboards documentation and reports in various environments including Snowflake Tableau and other visualisation tools
Build predictive models to forecast our fraud KPIs and evaluate against the budget and actuals
Collaborate with data engineering to build and maintain ETLs and data models relevant to the fraud and financial risk domain
Promote a datadriven culture across the business
Qualifications :
Basic Requirements
3 years of professional data analyst experience in a technical domain
Excellent analytical and problemsolving skills
Experience using a range of statistical methods such as time series analysis forecasting hypothesis testing A/B testing ANOVA regression analysis
Highly proficient in SQL and Tableau (or equivalent BI tool)
Experience working with large unstructured and heterogeneous data sources as well as the ability to write and understand complex SQL
Experience building ETL and/or using data transformation tools like DBT
Experience using Python for data analysis
Selfstarter comfortable in a fastpaced environment and able to adapt to changing circumstances quickly
Strong data storytelling skills capable of translating complex data into understandable conclusions and recommendations
Ability to think creatively and insightfully about business problems
Excellent written and verbal communication skills
Nice to have
Experience with data analysis in the financial crime domain (fraud AML etc.)
Bachelors degree in mathematics statistics or relevant experience in a related field
Additional Information :
The Perks
We trust you so we offer flexible working hours as long it suits both you and your team.
Physical and mental health support through our partnership with GymPass giving free access to over 1500 gyms in the UK 11 therapy meditation sessions digital fitness and nutrition apps.
CycletoWork Scheme.
Health and Life Insurance.
Pension Scheme.
25 days of Annual Leave ( Bank Holidays).
Possibility to travel to different offices around Europe.
Office snacks every day.
Friendly comfortable and informal office environment in Central London.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
