Top Tech Jobs & Startup Jobs in London

Analyze and improve patent data quality across families, ownership, legal status, and coverage. Define quality standards, build test sets, investigate anomalies and root causes, assess new data sources, review AI-assisted enrichment, document rules, and lead quality-improvement projects. The role combines patent expertise with hands-on SQL and Python analysis, automated testing, stakeholder communication, and continuous improvement of AI-ready data.

Own the enterprise IAM architecture roadmap across Saviynt, IGA, authentication, PAM, and human, non-human, and AI identities. Design integrations, access controls, SSO, MFA, federation, identity lifecycle processes, and least-privilege patterns. Guide engineers, review implementations, define readiness and audit evidence, manage exceptions, and support incident diagnosis. Collaborate with architects, developers, and the Product Owner while balancing security, cost, scalability, and operational risk.

Own AI-powered product capabilities from discovery through launch and adoption. Translate customer and business needs into requirements, prioritize backlogs, write user stories, define acceptance criteria, and collaborate with Engineering, Data Science, UX, and business teams. Support customer discovery, experimentation, testing, demonstrations, and continuous improvement while tracking product success metrics and promoting transparency, privacy, reliability, fairness, security, explainability, and customer trust.

Own complex analytics projects from business questions through delivery, developing reliable data products and solutions. Partner with product managers, analytics engineers, technologists, and senior stakeholders to shape data-driven strategy. Apply data preparation, blending, governance, and emerging AI techniques while coaching junior colleagues in analysis design, stakeholder engagement, and project management.

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.

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.

Uses patent data and analytics expertise to define, evaluate, and improve AI-assisted patent intelligence products. Responsibilities include creating evaluation standards, reviewing AI outputs, identifying data and reasoning issues, shaping product use cases, collaborating with engineering and product teams, and presenting recommendations to senior stakeholders. The role supports portfolio comparison, competitor benchmarking, technology trends, licensing, M&A, patent summaries, and claim interpretation.

Own the strategy, roadmap, development lifecycle, and go-to-market activities for fraud analytics products. Lead customer discovery, prioritize product improvements, analyze complex data, collaborate with development and data science teams, and use market and customer insights to improve user outcomes. The role requires fraud prevention expertise, statistical modeling and AI/machine learning knowledge, strong stakeholder communication, and flexible UK-US working hours.

Analyze complex insurance data to support business decisions, improve data quality, and resolve issues through validation, profiling, reconciliation, and root-cause analysis. Develop SQL queries, create Power BI reports, communicate insights to varied stakeholders, and support data onboarding, workflow automation, risk management, and process optimization. Collaborate with customers, data providers, and internal teams to improve operational efficiency and data lifecycle processes.

Own a product or significant area within Interfolio’s Faculty Information System. Develop product strategy and roadmaps, conduct customer discovery, prioritize opportunities, build business cases, identify AI opportunities, and guide products from concept through launch and ongoing improvement. Collaborate with faculty, researchers, institutional users, engineering, design, marketing, sales, customer success, and support while applying technical fluency across SaaS products, APIs, integrations, data, and architecture.