Top Tech Jobs & Startup Jobs in London

Develop and maintain Python and SQL research tools, analytics, data pipelines, automation, and AI-enabled workflows. Analyze and validate large financial datasets, investigate data issues, support quantitative investment and index research, and apply regression, optimization, factor analysis, risk modeling, and performance analytics. Collaborate across research, engineering, technology, and data operations teams while supporting index methodologies, rebalances, client inquiries, and continuous process improvement.

Leads DORA client audits and ISAE 3000 attestations, managing planning, evidence, external auditors, remediation, and final issuance. Oversees an assurance team, strengthens technology risk controls, maintains audit documentation, reports assurance metrics, and partners with Technology, Product, Security, Legal, Risk, Compliance, clients, and auditors. Drives audit readiness, control improvements, automation, standardization, and governance across a complex global data and analytics environment.

Owns cyber risk oversight for a Data & Analytics portfolio, assessing controls, architecture, threats, vulnerabilities, AI security, identity, cloud, third-party risk, and remediation. Partners with business, engineering, and central Cyber teams to translate technical risks into business impact, treatment options, and executive decisions. Maintains risk reporting, challenges security decisions, supports regulatory alignment, and builds trusted relationships across organizational boundaries.

Supports the strategy, roadmap, and delivery of LSEG’s Enterprise AI Platform. The role helps define platform capabilities, collaborate with Engineering and governance teams, gather requirements, prototype AI products, support platform adoption, track metrics, maintain standards, and coordinate with cloud and industry partners. It is designed for an early-career product manager interested in AI platforms, enterprise software, APIs, and responsible AI.

Supports the strategy, roadmap, and delivery of LSEG’s Enterprise AI Platform. Responsibilities include defining platform capabilities, partnering with Engineering and governance teams, gathering requirements, supporting AI infrastructure adoption, validating prototypes, tracking delivery and success metrics, maintaining standards and documentation, and coordinating with product teams, cloud providers, and industry partners. The role focuses on secure, scalable, governed AI enablement across the enterprise.

Own and improve Technology and Cyber control libraries and standards. Translate regulations and frameworks into control requirements, implementation guidance, evidence expectations, and mappings. Lead reviews, governance approvals, traceability, remediation tracking, audits, regulatory assessments, and RCSAs. Partner with control owners, security specialists, risk, and audit teams to challenge weaknesses. Use analysis, automation, and approved AI to improve data quality, duplicate detection, reporting, and workflow efficiency.

Leads real-time and post-trade supervision for LSE’s extended-hours market, managing trading halts, cancellations, disorderly events, investigations, escalations, and participant interactions. Develops procedures, playbooks, controls, and operational readiness processes for overnight supervision. Requires expertise in market structure, trading lifecycles, venue rules, UK and European regulations, and time-critical decision-making, along with strong leadership and stakeholder management skills. The role supports predominantly Asian-hour shifts from 12:00 to 08:00.

Leads commercial finance operations for Sales and Account Management, overseeing deal governance, pricing, profitability, risk, policy exceptions, annual price increases, and commercial process improvements. Partners with Finance, Sales, Legal, Product, Tax, Compliance, and Operations to support sound customer agreements and business decisions. Manages approximately 17 professionals across multiple regions, including resource planning, performance management, talent development, succession planning, and operational execution.

Analyze end-to-end operational processes using interviews, documentation, system data, SQL, Python, and process-mining insights. Identify automation, analytics, ML, and AI opportunities; quantify impact and feasibility; map as-is and to-be workflows; define KPIs and delivery-ready use cases; support prioritization, stakeholder communication, adoption, and value realization. The role works upstream of engineering to improve digitalization pipeline quality and ensure initiatives address real operational needs.

Leads the strategy, architecture, and delivery of scalable analytics engineering capabilities across pricing, risk, derived metrics, and predictive analytics. Oversees distributed systems, real-time and batch computation, AI/ML productionisation, engineering standards, and technical roadmaps. Partners with Product, Research, Commercial, and engineering teams while applying fixed income and derivatives expertise. Builds and scales a high-performing engineering organisation and drives enterprise-wide alignment and innovation.