Top Tech Jobs & Startup Jobs

Leads complex analytics projects, translating business questions into actionable insights and recommendations. Partners with senior stakeholders, develops metrics and reporting solutions, manages multiple priorities, collaborates cross-functionally, evaluates emerging analytics tools including AI-assisted techniques, and mentors junior analysts.

Develop and maintain software applications supporting author services. Responsibilities include translating business needs into software solutions, collaborating with developers for integration, improving engineering practices, and resolving complex bugs and technical issues within an Agile team.

Manage regional healthcare accounts with a primary focus on new sales and revenue growth. Develop account strategies, identify opportunities within existing customers, serve as the main client contact, coordinate internal delivery teams, and report performance to clients and leadership. The role requires consultative selling experience, strong negotiation and communication skills, executive-level engagement, and the ability to manage complex accounts in a matrixed organization.

Leads regional research sales across Southeast Asia, Australia, and New Zealand, managing Account Managers and driving new business, renewals, upselling, forecasting, complex negotiations, and revenue growth. Builds and coaches high-performing teams, develops strategic sales plans, manages key consortium and enterprise relationships, and collaborates across product, marketing, finance, pricing, and customer success in a complex matrix organization.

Develop and deploy production-grade AI and data science solutions for scientific discovery, including LLM applications, NLP, semantic search, RAG, agentic workflows, knowledge graphs, and recommendation systems. Lead model evaluation, experimentation, monitoring, and lifecycle management while collaborating with engineering, product, research, and domain teams. Influence technical strategy, mentor data scientists, and deliver reliable, scalable, evidence-grounded AI products.

Leads end-to-end implementation of clinical software across healthcare organizations, managing project plans, stakeholder engagement, requirements gathering, workflow analysis, EHR integrations, training, risks, documentation, and transition to Customer Success. Serves as the primary customer contact while coordinating technical and clinical teams to drive adoption, successful go-live, and continuous improvement.

Develop and maintain complex full-stack web applications using React and Node.js. Lead software through the full SDLC, from requirements and system design through deployment and maintenance. Build accessible, performant client-side applications, micro-frontends, and services; integrate frontend and backend components; and ensure quality through continuous integration, code reviews, and automated testing. Collaborate with Product, UX, engineering teams, and healthcare-domain professionals using Agile delivery practices.

Design, develop, and lead scalable generative AI services and reusable platform components using Python and Java. Drive architecture, engineering standards, distributed systems design, Kubernetes-based deployment, observability, testing, and CI/CD. Collaborate with product, platform, and research teams to productionize AI prototypes, resolve complex technical challenges, mentor engineers, and promote responsible AI integration.

Leads multiple complex implementation projects for nursing and health education customers, coordinating cross-functional teams from sales through delivery. Responsibilities include developing project plans, schedules, workflows, risk logs, and roadmaps; tracking milestones and KPIs; managing stakeholders, resources, issues, and customer expectations; facilitating meetings; improving processes; and providing post-project support. The role partners with Customer Success, Product, Sales, IT, Curriculum Solutions, and Support teams.

Provides technical direction and thought leadership across data science teams developing AI, NLP, and generative AI solutions. Sets architecture, quality, evaluation, governance, and responsible AI standards; guides LLM, RAG, retrieval, ranking, and recommendation systems. Reviews technical work, mentors teams, harmonizes tools and practices, and advises senior leadership on strategy, risk, compliance, and delivery.