Top Tech Jobs & Startup Jobs in Charlotte, NC

Lead product strategy and delivery for Commercial Banking data platforms, modernizing ERP ecosystems and reducing operational risk. Partner with engineering, design, and cross-functional teams to decompose legacy systems, build scalable backend solutions, enable client-facing capabilities, and drive profitability and operational controls.

The role involves leveraging technologies like Python and AWS to develop statistical and machine learning models, translating complex data insights into business goals, and working with a cross-functional team.

Own strategy and delivery of commercial money-movement products for a Top-10 commercial bank. Define product strategy, build digital platforms and features, collaborate with Tech and Design, reduce operational risk through controls and monitoring, and drive profitability and associate enablement.

Lead the vision and roadmap for a document intelligence platform, designing taxonomy and ontology, migrating to a graph-based architecture, enabling ML-driven extraction and chat-with-document experiences, and partnering across business lines to deliver compliant, discoverable, high-impact document products.

Lead development and delivery of GenAI/AI products for Commercial Banking. Define product specs, manage roadmaps, prioritize features, collaborate with data scientists, engineers, and cross-functional stakeholders, and serve as PM for a cross-functional pod to drive iterative quarterly delivery.

Lead product strategy and delivery for commercial banking technology products. Partner with tech, design, and business teams to build scalable solutions, improve operations, reduce risk, and enable profitability for loan, treasury, and capital markets products.

Lead policy development and governance for Commercial Bank risk; support regulatory change analysis, cross-border and country risk assessments, strategic reporting, operational excellence, continuity coverage, and stakeholder collaboration across Risk, Compliance, and Legal.

Lead development and evaluation of statistical and machine learning models to assess credit risk and challenge production models. Use Python, cloud, and big-data tools to analyze large numeric and textual datasets, partner with cross-functional credit risk and product teams, translate technical findings into business actions, and drive model validation, backtesting, and innovation.