Top Tech Jobs & Startup Jobs in Charlotte, NC

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.

Partner with technology leaders to manage resource investments, workforce planning, and third-party spend. Own governance, reporting, and the single source of resource data to support budgeting, hiring, contractor/vendor management, forecasting, and portfolio decision-making.

Design, develop, and deploy machine learning and AI solutions for HR and corporate systems. Partner with stakeholders to translate business needs into scalable analytics products, leverage cloud and modern AI tools, communicate insights to diverse audiences, and help establish responsible AI and model governance practices.

Lead and develop a team of fraud client services specialists to prevent fraud, resolve cases end-to-end, and optimize quality, productivity, and client experience. Partner with Fraud, Risk, Compliance, AML, and business stakeholders to implement new capabilities, drive process improvements, support workforce planning, and manage organizational readiness.

Technical lead responsible for architecting, building, and supporting cloud-native and legacy applications. Drive adoption of modern engineering practices, event-driven architectures, automation, and Generative AI tools. Mentor engineers, perform architecture and code reviews, ensure security and observability, troubleshoot production issues, and partner with stakeholders to deliver scalable, reliable solutions.