Senior Product Manager - Risk Monitoring (Basé à London)

Jobleads
London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Product Manager - AI, ML & Data Science

Senior Product Manager - AI, ML & Data Science

Senior Product Manager - AI, ML & Data Science

Senior Machine Learning Product Manager (Deploy)

Senior Product Data Scientist

Product Manager

  • Full-time

Company Description

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.

Job Description

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. The team aligns very closely with the Ops teams investigating suspicious activities.

As the product manager for the Customer Risk Monitoring team, you’ll work to create strong partnerships with technical and non-technical stakeholders to ensure alignment between our risk analytics roadmap and the business strategy. This role reports directly to the Head of Product.

You’ll be expected to work closely with data scientists, data analysts, engineers, and operations specialists, from individual contributors to heads of departments.

Job Purpose

As an Ongoing Monitoring Product Manager you will play a critical role in defining the standards to monitor the ongoing behaviour of our members to protect the financial services infrastructure from unwanted behaviour, enforce Teya policy, protect against fraud, and ensure Teya maintains compliance with AML regulations actively, supporting Teya’s commitment to prevent financial crime.

The role will cover transaction and other monitoring of member and their behaviour and external information about our members, and subsequent in-depth investigations of monitoring flags and risk issues and events. The monitoring team also performs periodic refreshes of KYB / KYC data held on members.

Key accountabilities

  1. Transaction and Member Monitoring.Create the team's training on suspicious behaviour and transaction patterns as well as roll your sleeves up and review alerts where required.
  2. KYC / KYB Refreshes.Advise on best practices in the area and be able to roll your sleeves up and conduct refreshes as required.
  3. Trend Analysis.Proactively analyse data on identified trends and suggest new transaction monitoring rules to the second line teams.
  4. Member Escalations.Manage escalation processes from the team within the first line and to the second line teams.
  5. Rule Setting.Be responsible for proposing, reviewing, and refining customer monitoring rules to enhance risk detection and mitigation. Continuously assess rule effectiveness and suggest improvements based on data insights and emerging trends.
  6. Collaborative Communication.Produce relevant reporting to senior management and build strong relationships with internal stakeholders, sharing insights and fostering a culture of ongoing monitoring risk management.
  7. Process & System Optimisation.Proactively identify potential areas of improvement and automations and work closely with the product and second line teams to scope and implement.
  8. Horizon Scanning.Keep abreast of upcoming regulation change and assess how it may impact upon departmental tasks and present suggestions to the second line teams.
  9. Strategic Support.Work closely with the First line operational risk leader and other areas of the First Line Operational risk function to assist in ad-hoc projects.

The role

Product Strategy and Roadmap.

Contribute to and drive the roadmap for fraud and money laundering prevention, aligning product goals with company objectives and managing trade-offs in metrics.

Develop and execute Go-To-Market (GTM) strategies, analyse issues in rollouts, and propose solutions.

Collaborate closely with data scientists and data analysts to define data requirements, evaluate model performance, and translate analytical insights into actionable product features.

Lead product discovery initiatives to keep our host ahead of industry standards and stay informed about market trends and competitor offerings.

Generate insights and analyse past trends, make data-driven decisions to inform product strategy.

Understand key engineering concepts such as SLAs, SLOs, availability, reliability, and test environments.

Balance technical debt management with new feature releases.

Utilise observability tools (logs and metrics) to monitor product performance.

Ensure the product meets European regulatory requirements (PCI, GDPR, Data Retention, etc.).

Stakeholder Management and Project Coordination.

Working with internal experts, including tech, sales, CR, security, compliance, tax, legal and accounting teams, ensuring products and services are secure, compliant, operational, and fit for purpose.

Manage external dependencies with key providers.

Identify and mitigate risks, build scenarios, and manage project timelines.

Using data to identify ancillary opportunities that allow us to serve merchants better.

Qualifications

Requirements

A minimum of 5 years of experience working in transaction monitoring / ongoing monitoring roles in payments and or business banking.

A deep understanding of the card acquiring and business banking space.

Strong knowledge of both the UK and EU AML regulations.

Excellent communication and teamwork skills.

Highly organized and unafraid to challenge and motivate both yourself and your team.

Highly motivated and enthusiastic individual who thrives working in a fast-paced environment.

Experience working with teams implementing data science and AI solutions.

Experience working on products and systems requiring to meet strong regulatory requirements and subject to regular audits.

Desired - An AML qualification such as ICA or ACAMS or equivalent.

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 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.

#J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.