National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Risk Data Analyst - Fincrime & Fraud Monitoring

Teya Services Ltd.
London
4 days ago
Create job alert

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.
Your Mission
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 cross-functionally with Compliance, Risk, Platform Engineering and product leaders to build and continuously improve the intelligence powering our detection and monitoring systems.
Job 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

Your Story
We’re looking for a Senior Data Analyst with a strong analytical foundation and a passion for tackling complex, ambiguous problems in the financial risk domain.
Must-haves
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 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

Nice-to-haves
Experience in acquiring services or the payments industry

Bachelor’s or Master’s 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 compliance-driven analytics environments

Fincrime certifications such as CAMS, ICA, or equivalent

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 withGymPassgiving free access to over 1,500 gyms in the UK, 1-1 therapy, meditation sessions, digital fitness and nutrition apps

Our company offers extended and improved maternity and paternity leave choices, giving employees more flexibility and support

Cycle-to-Work Scheme

Health and Life Insurance

Pension Scheme

25 days of Annual Leave (+ Bank Holidays)

Office snacks every day

Friendly, comfortable and informal office environment in Central London

Teya is proud to be an equal opportunity employer.
We are committed to creating an inclusive environment where everyone regardless of race, ethnicity, gender identity or expression, sexual orientation, age, disability, religion, or background can thrive and do their best work. We believe that a diverse team leads to better ideas, stronger outcomes, and a more supportive workplace for all.
If you require any reasonable adjustments at any stage of the recruitment process whether for interviews, assessments, or other parts of the application—we encourage you to let us know. We are committed to ensuring that every candidate has a fair and accessible experience with us.

#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Investment Risk Analyst

Senior Data Analyst | Cambridge | Fintech

Senior Performance & Data Analyst

Senior Data Analyst

Senior Data Analyst (Families First)

Associate Data Analyst

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

LinkedIn Profile Checklist for Data Science Jobs: 10 Tweaks to Elevate Recruiter Engagement

Data science recruiters often sift through dozens of profiles to find candidates skilled in Python, machine learning, statistical modelling and data visualisation—sometimes before roles even open. A generic LinkedIn profile won’t suffice in this data-driven era. This step-by-step LinkedIn for data science jobs checklist outlines ten targeted tweaks to elevate recruiter engagement. Whether you’re an aspiring junior data scientist, a specialist in MLOps, or a seasoned analytics leader, these optimisations will sharpen your profile’s search relevance and demonstrate your analytical impact.

Part-Time Study Routes That Lead to Data Science Jobs: Evening Courses, Bootcamps & Online Masters

Data science sits at the intersection of statistics, programming and domain expertise—unearthing insights that drive business decisions, product innovation and research breakthroughs. In the UK, organisations from fintech and healthcare to retail and public sector are investing heavily in data-driven strategies, fuelling unprecedented demand for data scientists, machine learning engineers and analytics consultants. According to recent projections, data science roles will grow by over 40% in the next five years, offering lucrative salaries and varied career paths. Yet many professionals hesitate to leave their current jobs or pause personal commitments for full-time study. The good news? A vibrant ecosystem of part-time learning routes—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn data science while working. This comprehensive guide explores every pathway: foundational CPD units and short courses, hands-on bootcamps, accredited online MScs, plus funding options, planning strategies and a real-world case study. Whether you’re an analyst looking to formalise your skills, a software developer pivoting into data or a manager seeking to harness data-driven decision-making, you’ll find the right route to fit your schedule, budget and career goals.

The Ultimate Assessment-Centre Survival Guide for Data Science Jobs in the UK

Assessment centres for data science positions in the UK are designed to replicate the multifaceted challenges of real-world analytics teams. Employers combine psychometric assessments, coding tests, statistical reasoning exercises, group case studies and behavioural interviews to see how you interpret data, build models, communicate insights and collaborate under pressure. Whether you’re specialising in predictive modelling, NLP or computer vision, this guide provides a step-by-step roadmap to excel at every stage and secure your next data science role.