Top Tech Jobs & Startup Jobs in Charlotte, NC

Lead and scale a client experience research organization: set vision and strategy, hire and develop teams, establish rigorous research practices, partner with cross-functional leaders, guide qualitative and quantitative programs, synthesize insights into strategic recommendations, and advance research capability and governance across channels and products.

Lead strategy and roadmap for performance and reporting products, manage end-to-end delivery, translate data into client-facing digital experiences, ensure regulatory compliance with OGC, oversee vendors/consultants, and drive Agile execution and stakeholder alignment across the enterprise.

Advise ultra-high-net-worth clients on advanced estate planning, income tax, and financial planning. Analyze client documents, develop solutions and deliverables, partner with advisors, improve processes, support compliance, and participate in projects.

Advise ultra-high-net-worth clients on advanced estate planning, income tax, and financial planning. Analyze client documents, create deliverables, collaborate with advisors, mentor colleagues, contribute thought leadership, improve processes, ensure compliance, support projects, and travel for training and client meetings.

Partner with marketing analytics leadership to improve team effectiveness, design operating rhythms, manage cross-functional projects and dependencies, prepare concise updates and presentations, coordinate strategic priorities and OKRs, and build analytics domain fluency to drive follow-through and accountability.

Lead complex analytics projects supporting client experience transformation: gather and validate structured and unstructured data, apply advanced analytics and machine learning, produce executive visualizations and recommendations, manage recurring reporting, enforce data quality standards, and mentor other analysts to drive business decisions and improve client outcomes.

Lead end-to-end analytics for Flagship Client and Distribution: partner with stakeholders to frame problems, perform advanced analyses and machine learning, ensure data quality, develop recurring analytics products and executive visualizations, and mentor analysts to drive data-driven decisions.

The Manager, Machine Learning Engineer leads AI/ML initiatives, manages teams, oversees model development, and ensures alignment with business objectives.

Define and execute hybrid infrastructure architecture and roadmaps across on‑prem and cloud. Create reference architectures, lead integration and governance, ensure availability/security/resilience, evaluate tradeoffs, and communicate with executives to drive enterprise‑scale solutions.

Lead the development of executive talent management practices to enhance succession planning, enhance inclusivity, and improve decision-making across the organization.