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Tech Stack
Tools & technologiesPythonSQL
About the role
Key responsibilities & impact- Contribute to AI-powered tools that address key finance challenges including close cycle optimization, forecasting accuracy, and reporting automation
- Generate actionable insights for Controllership, FP&A, Tax, Treasury, AP, and AR teams
- Orchestrate the transition from traditional finance reporting to dynamic, AI-enabled reporting and analytics
- Partner with finance stakeholders at all levels to identify processes ripe for AI-driven transformation; document current-state workflows, pain points, and requirements
- Serve as a collaborative partner between the GFS team, Finance operations, and IT data teams
- Translate finance data and platform outputs into AI-ready formats and pipelines
- Help define and execute on data requirements for finance AI use cases across close, consolidation, planning, forecasting, tax, and treasury
- Support deployment and iteration of generative AI and agentic AI use cases tailored to finance workflows
- Author and maintain complex prompt libraries for Claude, Microsoft Copilot, and ChatGPT to support finance process automation, report generation, and intelligent document processing
- Evaluate and test prompt effectiveness across tools and finance use cases
- Design and build AI agent workflows that autonomously execute finance tasks such as data validation, reconciliation checks, variance analysis, and exception handling
- Build AI-powered dashboards, reports, and guided workflows
- Leverage Snowflake features including Cortex AI for finance analytics and AI-powered insights
- Support the optimization of OneStream AI Forecasting, AI Studio, Agentic AI, and Genesis capabilities within the EPM platform
- Collaborate with OneStream developers to enhance platform capabilities, training materials, and documentation utilizing AI tools
- Actively pursue skill growth in machine learning, AI governance, and advanced AI tooling
- Contribute to AI governance practices, development of AI safeguards, and compliance with regulatory requirements (SOX, GDPR, EU AI Act)
- Work closely with GFS leadership to develop enterprise standards based on best practice and ethical use of AI in Finance, aligned with IT governance
- Document all models, processes, and solutions with clear technical and user-facing documentation
- Cross-train with team resources to ensure business continuity.
Requirements
What you’ll need- 3–5 years of experience in data engineering, analytics engineering, AI development, or a closely related technical role
- Solid foundational knowledge of AI technologies including generative AI, agentic AI, and machine learning (data science familiarity is preferred)
- Demonstrated experience with agentic and generative AI tools (Claude, ChatGPT, Copilot) in a professional setting
- Proficiency in Python coding for data manipulation, workflow development, and AI/ML model building
- Proficiency in SQL and experience with the Snowflake data platform
- Demonstrated ability to write complex, multi-step prompts for LLM tools
- Experience supporting finance initiatives or working closely with finance teams on technology-driven projects
- Comfortable working with finance professionals at all levels — from analysts to senior leadership — to identify, document, and scope AI opportunities
- Strong communication skills with the ability to collaborate across technical and non-technical audiences.
Benefits
Comp & perks- Equal Employment Opportunity (EOE/M/F/Vets/Disabled) employer
- Building from within
- Taking care of each other
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data engineeringanalytics engineeringAI developmentgenerative AIagentic AImachine learningPythonSQLprompt engineeringfinance process automation
Soft Skills
collaborationcommunicationdocumentationcross-trainingstakeholder engagementproblem-solvingorganizational skillsadaptabilityteamworkleadership
