Top Tech Jobs & Startup Jobs

Design, develop, and validate statistical and machine learning models for auto insurance risk using large, distributed datasets. Partner with product and vertical teams to create new solutions, support existing models, deliver actionable insights, lead small projects, and mentor junior staff. Use Python and analytic tools to translate analyses into business recommendations.

Senior consulting data engineer responsible for leading complex data engineering projects, coding robust solutions, designing complex data models, troubleshooting and optimizing data operations, mentoring engineers, interfacing with customers and cross-functional teams, and ensuring quality through testing, code reviews, and performance tuning to deliver on-time, on-budget solutions.

Lead and manage data engineering teams to build and maintain high-quality data pipelines, implement automation and performance scripts, integrate LLMs/Agentic AI, collaborate with product and engineering, oversee data modeling, ensure data quality, and support SEC-related data solutions.

Lead and deliver cross-business strategic engagements: structure problems, perform qualitative and quantitative analysis, produce decision-ready materials for senior leadership, develop market and technology insights (including AI), foster RELX-wide strategy community, and share best practices across product and commercial teams.

Design, build, evaluate, and scale production-ready AI solutions (LLMs, NLP, retrieval, RAG, knowledge graphs) to support scientific discovery. Lead architecture, mentor data scientists, partner with engineering and product, and measure model quality, trustworthiness, and user impact.

Lead a team of engineers (six direct reports) to define technical strategy and execution for the CK AI Service. Own design and governance of RAG workflows, API expansion, system resilience, delivery velocity, standardization, mentoring, and cross-functional collaboration with Data Science to build production AI-powered services.

Licensed MD applies clinical expertise to extract, model, validate, and maintain clinical relationships for a healthcare knowledge graph. Works with data scientists and SMEs to build training datasets, support CDS product development, ensure clinical accuracy, and provide analytics and evidence-based insights to improve search, discovery, and point-of-care workflows.

Lead design, build, and operation of scalable AI/ML systems (LLM infrastructure, RAG pipelines, autonomous agents). Provide architecture and code guidance, establish ML engineering best practices, CI/CD, safety guardrails, evaluation frameworks, and ensure compliance with data governance and responsible AI standards.

Design, build, and maintain CI/CD pipelines and cloud infrastructure on Azure. Implement IaC, deploy containerized applications with Docker/Kubernetes, monitor systems, integrate DevSecOps, participate in on-call rotations, and document operational processes.

Partner with corporate legal departments to design and implement AI-driven workflows and LexisNexis solutions. Conduct demos, trainings, executive briefings, and workshops; advise on AI adoption and governance; identify expansion opportunities; collect client feedback and relay product recommendations. Travel frequently to support client engagements.