Senior Data Analyst - Fraud Prevention

Hello! We're Teya.

Teya is a payment and software service provider, headquartered in London serving small, local businesses across Europe. Founded in 2019, we build easy to use, integrated tools that enable our members to accept payments and boost business performance.

At Teya we believe small, local businesses are the lifeblood of our communities.

We’re here because we don’t believe there’s a level playing field that gives small businesses with a fighting chance against the giants of the high street. We’re here because we see banks and legacy service providers making things harder for them. We don’t think the best technology or the best service should be reserved for those with the biggest headquarters. We’re here to fight for a future where small, local businesses can thrive, and to commit the same dedication they offer all of us.

Become a part of our story.

We’re looking for exceptional talent to join our mission. We offer a chance to create impact in a high-energy 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 in-house 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 long-term 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:

1. 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.
2. Be a key individual contributor to a diverse and innovative team, developing a deep understanding of data inputs and driving continuous improvement while addressing fast-moving risks and opportunities.
3. Work with senior product, business, and engineering leaders to analyse data, identify opportunities for building new models, develop and maintain real-time dashboards, and deliver insights through in-depth reports.
4. Effectively manage business stakeholders and drive initiatives to promote actionable insights, identifying and prioritising requirements and owning a roadmap of deliverables.
5. Build and maintain dashboards, documentation and reports in various environments, including Snowflake, Tableau and other visualisation tools.
6. Build predictive models to forecast our fraud KPIs and evaluate against the budget and actuals.
7. Collaborate with data engineering to build and maintain ETLs and data models relevant to the fraud and financial risk domain.
8. Promote a data-driven culture across the business.

Qualifications

Basic Requirements:

1. 3+ years of professional data analyst experience in a technical domain.
2. Excellent analytical and problem-solving skills.
3. Experience using a range of statistical methods, such as time series analysis, forecasting, hypothesis testing, A/B testing, ANOVA, regression analysis.
4. Highly proficient in SQL and Tableau (or equivalent BI tool).
5. Experience working with large, unstructured and heterogeneous data sources, as well as the ability to write and understand complex SQL.
6. Experience building ETL and/or using data transformation tools like DBT.
7. Experience using Python for data analysis.
8. Self-starter, comfortable in a fast-paced environment and able to adapt to changing circumstances quickly.
9. Strong data storytelling skills, capable of translating complex data into understandable conclusions and recommendations.
10. Ability to think creatively and insightfully about business problems.
11. Excellent written and verbal communication skills.

Nice to have:

1. Experience with data analysis in the financial crime domain (fraud, AML, etc.).
2. Bachelor's degree in mathematics, statistics, or relevant experience in a related field.

Additional Information

The Perks:

1. We trust you, so we offer flexible working hours, as long it suits both you and your team.
2. Physical and mental health support through our partnership with GymPass giving free access to over 1,500 gyms in the UK, 1-1 therapy, meditation sessions, digital fitness and nutrition apps.
3. Cycle-to-Work Scheme.
4. Health and Life Insurance.
5. Pension Scheme.
6. 25 days of Annual Leave (+ Bank Holidays).
7. Possibility to travel to different offices around Europe.
8. Office snacks every day.
9. Friendly, comfortable and informal office environment in Central London.