Top Tech Jobs & Startup Jobs in London

Lead product analytics for customer onboarding and account access. Derive insights from data, guide product decisions, partner with product managers, engineers, and designers, and identify opportunities to improve customer experience while preventing fraud. Build data pipelines, dashboards, and KPI reporting systems; communicate findings across teams; and explore AI-driven automation and machine learning techniques to improve analytics and generate insights.

Lead product analytics for Wise’s Send tribe, focusing on verification, transfer predictability, service quality, customer retention, and growth. Analyze customer problems, define KPIs, conduct A/B tests and causal analyses, track product impact, and guide prioritization with Product Managers and stakeholders. The role also supports scaling service operations, improving customer journeys, and identifying opportunities through SQL and Python analysis, with optional use of Airflow, dbt, Looker, and predictive modeling.

Lead product analytics for Wise’s Business Account Management Team. Derive insights, define KPIs, guide product strategy, evaluate opportunities, improve A/B testing, and build automated data pipelines and dashboards. Own complex cross-team analyses involving fraud, chargeback risk, pricing, and product decisions. Communicate findings clearly, influence stakeholders, and enable fast, data-driven decision-making.

Global People Partner supporting Payment Operations and Product Operations across seven locations. The role partners with senior leaders on people strategy, talent planning, succession, organizational design, workforce planning, engagement, DEI, employee relations, and organizational change. It analyzes people metrics, leads engagement survey action plans, supports leadership development, advises on complex employee relations matters, and collaborates with HR centers of expertise and recruitment teams to support global business growth.

Lead product analytics for Wise’s business onboarding experience. Own KPI frameworks, conduct funnel and cohort analysis, lead A/B testing, build dashboards and governed data products, and recommend product improvements that balance conversion, customer experience, operational efficiency, and risk. Develop LLM-ready data foundations with clear entities, schemas, metadata, documentation, and governance while partnering with product managers, engineers, designers, and verification teams.

Lead the architecture and production deployment of deep learning and machine learning systems for real-time financial crime detection. Design sequence-based, graph-based, and attention-based models; establish reusable experimentation-to-production pipelines; evaluate foundation models and embeddings; make architecture decisions under latency and throughput constraints; partner with data scientists on evaluation and measurement; and mentor engineers and data scientists.

Lead development and deployment of machine learning and Generative AI systems for AML operations. Responsibilities include building EDD LLMs, evaluation datasets and automated testing frameworks, prompt optimization, shadow testing, production monitoring, human-in-the-loop workflows, and financial crime prevention solutions. The role also provides technical leadership, mentorship, architectural guidance, and cross-functional collaboration.

Own and enhance AML control design and risk detection strategy across Wise’s global products. Partner with Product and Engineering teams to implement compliant, scalable controls, improve automation and detection quality, reduce customer friction, and assess control effectiveness through data and testing. Translate regulatory developments into product requirements, support financial crime risk assessments, and lead remediation projects arising from audits, incidents, and regulatory feedback.

Drive IT SOX scope rationalization, dependency mapping, RACM development, and control optimization across cloud and SaaS environments. Support ITGC and ITAC testing, onboard new systems, document system dependencies, and partner with Finance, Risk, Security, and Platform stakeholders. Translate technical architecture and cloud-native processes into audit-ready documentation while identifying redundant or missing controls.

Design and maintain scalable Java and Spring Boot backend services in an event-driven microservices architecture. Own public API standards, authentication systems, SDKs, and developer infrastructure while ensuring security, reliability, and excellent partner integration experiences. Provide technical leadership through architecture, code reviews, domain modeling, mentoring, and cross-functional collaboration. Help global engineering teams align with API standards and architecture patterns, with travel to international engineering hubs.