Top Tech Jobs & Startup Jobs in London

Leads the global and local publishing strategy for Clinical Solutions content, including medical reference books and digital products. Oversees portfolio roadmaps, proposals, financial performance, localization, platform integration, market analysis, and content pipelines. Partners across business units and regions, supports electronic solutions and translations, manages costs and margins, tracks performance metrics, and coaches team members in a matrixed global environment.

Leads multiple distributed engineering teams supporting SciVal’s large-scale research analytics platform. Sets technical strategy, architectural standards, and roadmap execution across frontend, backend, data, and quality engineering. Develops engineering leaders, manages workforce planning, and drives platform modernization, reliability, security, and operational resilience. Partners with Product, Data, Architecture, UX, customers, and commercial stakeholders to deliver analytics, AI-assisted, search, and agent-ready capabilities.

Design, build, and deploy ML-powered services, APIs, microservices, and full-stack tools for fraud and identity analytics. Integrate models into real-time production, implement automated training/monitoring workflows, own DevOps and security for services, and collaborate with data scientists, architects, and QA.

Leads ICIS’s operational reliability function, managing SRE team leaders and engineers while improving production resilience, observability, automation, incident response, disaster recovery, and service reliability. The role sets operational priorities, oversees post-mortems and corrective actions, balances operational and security work, communicates risks across technology and business teams, and advances AI-enabled operations. Participation in on-call support and major incident response is expected.

Leads the UK&I Data Engineering team, setting technical strategy and overseeing delivery of data products, ingestion pipelines, reporting solutions, and customer-facing capabilities. Drives Azure and Databricks cloud modernization, data governance, security, privacy, compliance, and AI adoption. Responsibilities include team leadership, talent development, workforce planning, cross-functional stakeholder management, and collaboration with global engineering, product, analytics, architecture, and operations teams.

Leads global data acquisition for fraud and identity products, focusing on mobile identity and phone intelligence. Manages strategic data supplier relationships, evaluates and onboards external data assets, negotiates contracts, oversees governance and performance, and partners with product, legal, compliance, finance, analytics, and technology teams. Develops business cases and ensures acquisition activities meet regulatory, risk, operational, and commercial requirements.

Supports the Senior Product Manager in shaping and delivering enhancements for SSRN, Elsevier’s preprint server. Responsibilities include writing user stories and acceptance criteria, gathering requirements, managing the product backlog, supporting Agile sprint ceremonies, tracking releases in JIRA and Aha, prioritizing defects, producing analytics reports, and assisting with discovery, launch readiness, and stakeholder communications.

Lead and expand relationships with a small number of high-value insurance clients, drive retention and revenue through strategic account plans, cross-sell/upsell, forecasting, and C-suite engagement. Coordinate internal teams, inform product roadmap with client insights, ensure service delivery, and represent the company at industry events. Requires frequent travel.

Drive new partner sales and revenue growth in DACH by prospecting, building pipeline, managing territory plans, converting leads to closed contracts, forecasting, and supporting onboarding and retention in collaboration with presales and partner success teams.

Lead customer-facing data science and AI projects for commodity markets: identify high-impact opportunities, prototype and deploy ML/AI solutions (including LLMs and agentic approaches), measure business impact, collaborate with product, engineering and domain experts, and share learnings to shape ICIS data and AI products.