Finance Transformation AI Manager

Responsibilities Lead end-to-end delivery of finance AI solutions, including planning, execution, monitoring, and stakeholder reporting Design and deploy predictive, generative, and optimization models for finance use cases (close acceleration, forecasting, anomaly detection, reconciliations, working capital optimization) Architect data pipelines and feature engineering frameworks supporting financial datasets Supervise, coach, and mentor staff, review work products and ensure adherence to quality standards Translate complex technical outputs into business insights for finance users Manage engagement budgets, timelines, and resource allocations Collaborate with client stakeholders to understand operations and align deliverables with business objectives Support proposal development, solution demonstrations, and business development initiatives Lead proposal development and business development collateral development Maintain strong client relationships and act as a trusted advisor Stay current with emerging AI technologies and finance regulations impacting client environments Demonstrated ability to manage multiple priorities and simultaneous projects Strong interpersonal, communication, and client-service skills Commitment to professional development and continuous learning Meet or exceed targeted billing hours (utilization) Other duties as assigned Qualifications Bachelor’s or Master’s degree in Data Science, Computer Engineering with minor in Finance, Accounting, or related field 6+ years of progressive experience in analytics, finance transformation, or advisory roles Ability to communicate complex technical concepts clearly to non-technical stakeholders Experience working directly with client personnel at multiple organizational levels Experience implementing AI solutions for finance functions Rapid prototype development using Replit, Cursor or similar platform Knowledge of finance processes, accounting, reporting frameworks, and regulatory environments AI/ML: Agentic AI, LLMs, predictive modeling, NLP, time-series forecasting, optimization Programming: Python, SQL, or equivalent data languages Data Platforms: Azure, AWS, Snowflake, Databricks, GCP Finance Systems: Financial data warehouses, EPM, ERP integration Data Engineering: ETL pipelines, data modeling, query optimization Willingness to travel up to 30% Note: This description focuses on the role's core responsibilities and qualifications. For specifics on compensation, benefits, and equal opportunity statements, refer to official company documentation. #J-18808-Ljbffr Grant Thornton (US)