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.
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