Role Summary
Tyme is seeking an experienced and technically fluent Product Owner and Financial Crime strategist to lead the development and optimisation of our Financial Crime risk platforms. This strategic role covers the full spectrum of financial crime domains — including fraud prevention and detection, Anti-Money Laundering (AML), transaction monitoring, sanctions screening, and KYC/CDD processes, suited to one that is passionate about fighting financial crime with real-time, intelligent decisioning, and platform innovation.
You will act as the internal owner of key risk platforms, working across operations, compliance, data, and engineering teams to deploy, manage and evolve capabilities that protect Tyme. This role is ideal for someone passionate about combining product ownership, highly analytical thinking, regulatory awareness, and cutting-edge technical expertise to fight financial crime at scale.
Why This Role
This is a strategic, hands-on position for someone passionate about shaping our approach to financial crime from the inside out. You’ll be Tyme’s primary enabler of their financial crime platform—balancing technical depth, financial crime acumen, and product thinking to ensure we stay one step ahead of adversaries. Your work will directly impact customer safety, financial integrity, and Tyme’s brand trust.
Key Responsibilities
- Platform Ownership & Product Leadership:
- Act as the internal product owner for our Financial Crime risk platforms, including systems for fraud detection, AML transaction monitoring, sanctions, PEP screening and customer risk assessment.
- Translate Tyme’s financial crime risk strategies into actionable product roadmaps and configuration plans across front-end, back-end, and API integrations.
- Manage a unified backlog of feature enhancements and configuration requests for fraud, AML, and compliance use cases, aligned with business and regulatory priorities.
- Lead testing and deployment of platform updates in collaboration with technical vendors and internal teams.
- Ensure that data sources (e.g. transaction data, KYC data, behavioural signals) are correctly ingested and profiled for use in both fraud and AML systems.
- Financial Crime Strategy & Decisioning
- Develop our end-to-end financial crime strategy, spanning from prevention & detection plan to risk appetite, customer journeys and product features
- Develop and refine the end-to-end financial crime platform, including for investigations and resolutions
- Design and implement the risk decisioning logic and detection rules for customer risk assessment, fraud, AML, and other financial crime risks (e.g. velocity thresholds, behavioural scoring, name matching).
- Monitor data to detect emerging threats such as account takeovers, duplicate accounts creation, social engineering, and mule activity, and partner with analytics and fraud operations to address the threats.
- Collaborate with analytics, engineering, and compliance to tune policy changes or deploy new controls
- Work with fraud and AML operations teams with investigations into financial crime incidents, such as on incident response workflows and, deep-dive investigations into new attack vectors.
- Partner with risk, data scientists, and operations teams to iterate prevention and detection strategies.
- Lead and mentor a small team of fraud intelligence analysts, driving both tactical response and long-term prevention strategy.
- Analytics & Operational Tuning
- Conduct exploratory data analysis to derive insights from user behaviour and transaction patterns.
- Write, test, perform root cause analysis, quantify outcomes, and optimize risk rules (e.g., based on velocity, biometrics, location, device fingerprinting) using SQL / Python or similar language.
- Work with data science to incorporate machine learning models into financial crime pipelines.
- Develop internal dashboards and visual reports to communicate insights, trends and impact.
- Lead periodic reviews with internal stakeholders to align roadmap and share insights.
- Stakeholder Collaboration & Enablement
- Syndicate the financial crime strategic approach and posture, to key stakeholders involved in financial crime, achieving buy-in and alignment in the process
- Serve as the primary interface between engineering, analytics, compliance, customer servicing, and external platform providers.
- Provide documentation, enablement materials, and best practices to support case analysts and investigators.
- Drive cross-functional initiatives, such as unified customer risk profiling and event lifecycle management (from onboarding to ongoing monitoring).
Requirements
Ideal Candidate Profile
- Experience & Domain Knowledge
- 5+ years of experience in fraud operations, AML transaction monitoring, financial crime technology, or risk analytics within fintech, banking, or payments.
- Solid understanding of financial crime typologies including account takeovers, mule accounts, social engineering, money laundering schemes, structuring, and trade-based ML.
- Experience configuring or managing financial crime systems such as fraud platforms (e.g., ThreatMetrix, Threatmark, Quantexa), AML tools (e.g., Actimize, FICO, SAS), and sanctions screening platforms.
- Demonstrated success in managing cross-functional technology projects involving data science & analytics, engineering, and operations, to develop test and optimise decision systems
- Technical Fluency
- Deep understanding of web and app infrastructure: JavaScript, APIs, cookies, HTML, browser behaviour, and fraud signal instrumentation.
- Solid command of SQL and analytical tools for querying behaviour datasets and tuning rule logic.
- Proficiency in Python, JavaScript/TypeScript, or Rust for scripting, rules testing, and automation.
- Ideally, some experience with serverless compute environments (e.g., AWS Lambda, CloudFront, Cloudflare, Akamai) and DNS/CDN setup
- Leadership & Communication
- Strong stakeholder engagement skills, capable of aligning fraud and AML initiatives across technical and non-technical audiences, and able to articulate the risk rationale behind rules, and product trade-offs.
- Demonstrated leadership in managing incident response, mentoring analysts, and driving long-term strategy.
- Comfortable working in agile product teams, with tools such as Jira, Confluence, and Figma.
Preferred Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related technical field.
- Background in AI, data science, or cybersecurity is a plus.
- Awareness of regulatory standards including GDPR, AFASA, and local PII/data handling legislation.
- Experience with behavioural biometrics, session intelligence, and device fingerprinting frameworks.
Benefits
- Competitive salary that recognizes your talent and potential
- Performance-based bonus, including stock-based incentives for high performers
- Conferences and expert-led training to accelerate your career
- Flexibility to work from home or the office
- Generous annual leave allowance, and paid day off for your birthday
- Meal and parking allowances
