Top Tech Jobs & Startup Jobs in Charlotte, NC

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

Lead development of workplace retirement offers and strategies from vision through execution. Conduct market, competitive, financial, and customer analysis; define and prioritize offer portfolios; align stakeholders across digital, operations, marketing, client relationship, risk, and legal to deliver participant-focused solutions, especially for the Crossover Rollover initiative.

This role requires transforming complex data into actionable insights for senior leadership, utilizing tools like Tableau and SQL, and overseeing analytical projects.

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.

As a Senior Reliability Engineer, you will enhance resiliency practices, resolve incidents, automate infrastructure management, and contribute to architectural decisions.

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.

As Head of Competitive Intelligence for Personal Wealth, you will establish a new function to guide strategic decisions through competitive insights and industry trends, while leading a team and influencing senior stakeholders.

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.