FP&A- Data Science & AI Enablement

As a modernizing Finance team, you will bring data science, machine learning, and AI into FP&A to improve forecasting and reporting processes. Your role is to transition analysts from manual, spreadsheet-heavy work to automated, AI-assisted workflows and build forecasts, dashboards, and AI assistants to enhance Finance's collaboration with the business. Key Responsibilities: - Build the FP&A data foundation by consolidating GL, planning, sales, T&E, and procurement data into a reliable finance dataset in Snowflake. - Modernize forecasting and scenario planning by replacing static budgets with driver-based forecasts and building scenario models for quick decision-making. - Integrate AI assistants into FP&A workflows to automate tasks, draft commentary, and summarize results with a human review step. - Identify anomalies early on by developing models that flag unusual postings, outlier expenses, and forecast drift to address issues proactively. - Collaborate across the business to translate Finance priorities into practical data solutions, coordinate with IT, Data, and Security, and facilitate understanding for non-technical stakeholders. - Support team growth by conducting workshops on SQL, Python, no-code/low-code tools, and AI agents to enhance confidence in using these tools. - Ensure complex tools are user-friendly and accessible to colleagues with varied technical backgrounds to promote demystification. - Uphold governance standards for AI use, certified data sources, model explainability, audit trails, and access controls in alignment with SOX requirements. Required Qualifications: - Bachelor's or Master's degree in Finance, Economics, Accounting, Data Science, Statistics, Computer Science, Engineering, Mathematics, or related quantitative field. - 3 to 6 years of hands-on experience with Python and SQL in FP&A, finance analytics, or technical consulting. - Practical experience in building forecasting, classification, or anomaly-detection models and implementing them. - Proficiency in working with cloud data warehouses, modern data pipelines, LLMs, and Power BI for reporting. - Knowledge of finance controls, SOX compliance, and audit trails in analytical and AI-enabled environments. Preferred Qualifications: - Familiarity with Snowflake, Planful, Salesforce, SAP Business One, Expensify, Procurify, or similar systems. - Experience with no-code/low-code tools and AI agents for finance applications. - Understanding of data governance, privacy, security, and LLM usage. - Previous exposure to manufacturing or distribution business processes is advantageous. As a modernizing Finance team, you will bring data science, machine learning, and AI into FP&A to improve forecasting and reporting processes. Your role is to transition analysts from manual, spreadsheet-heavy work to automated, AI-assisted workflows and build forecasts, dashboards, and AI assistants to enhance Finance's collaboration with the business. Key Responsibilities: - Build the FP&A data foundation by consolidating GL, planning, sales, T&E, and procurement data into a reliable finance dataset in Snowflake. - Modernize forecasting and scenario planning by replacing static budgets with driver-based forecasts and building scenario models for quick decision-making. - Integrate AI assistants into FP&A workflows to automate tasks, draft commentary, and summarize results with a human review step. - Identify anomalies early on by developing models that flag unusual postings, outlier expenses, and forecast drift to address issues proactively. - Collaborate across the business to translate Finance priorities into practical data solutions, coordinate with IT, Data, and Security, and facilitate understanding for non-technical stakeholders. - Support team growth by conducting workshops on SQL, Python, no-code/low-code tools, and AI agents to enhance confidence in using these tools. - Ensure complex tools are user-friendly and accessible to colleagues with varied technical backgrounds to promote demystification. - Uphold governance standards for AI use, certified data sources, model explainability, audit trails, and access controls in alignment with SOX requirements. Required Qualifications: - Bachelor's or Master's degree in Finance, Economics, Accounting, Data Science, Statistics, Computer Science, Engineering, Mathematics, or related quantitative field. - 3 to 6 years of hands-on experience with Python and SQL in FP&A, finance analytics, or technical consulting. - Practical experience in building forecasting, classification, or anomaly-detection models and implementing them. - Proficiency in working with cloud data warehouses, modern data pipelines, LLMs, and Power BI for reporting. - Knowledge of finance controls, SOX compliance, and audit trails in analytical and AI-enabled environments. Preferred Qualifications: - Familiarity with Snowflake, Planful, Salesforce, SAP Business One, Expensify, Procurify, or similar systems. - Experience with no-code/