Description
Overview of the Role
The Finance & Strategy (F&S) team serves as a trusted advisor to the business to help inform and guide decision-making through business partner support and insightful analyses.
We are looking for a Financial Planning & Analysis (FP&A) Topline Analytics & AI Director within the Corporate FP&A team to play a key role in shaping the future of topline forecasting & analytics, and in developing data driven financial insights. You will work with large-scale financial and operational datasets, applying advanced machine learning (ML) and AI techniques to influence the topline growth trajectory.
The role sits at the intersection of FP&A/Finance, Data Science & Engineering, and Data/Operations. You will partner within Finance and cross-functionally to deliver predictive machine learning models and drive a step-change in topline analytics and forecasting by combining advanced machine learning and generative/agentic AI approaches. You will also contribute to the evolution of Finance AI capability development, including vision, strategy & roadmap.
Responsibilities
Own/Lead AI based topline forecasting, analytics and reporting automation.
Be the topline analytics engine: Collaborate with FP&A/Finance, Data Science & Engineering and Data/Operations teams to deliver topline forecasting and business insight automation at scale.
Drive ML Model development for bookings/attrition/revenue forecasting and incorporate it into the broader forecasting rhythm.
Lead and pave the path forward for advanced analytics using AI and ML to drive a step-change in topline forecasting and insight generation / reporting.
Experiment and ideate to evaluate topline business drivers, model features and new data sources, including use of Generative/Agentic AI approaches in conjunction with ML to improve AI output accuracy.
Drive business impact by translating complex data findings into actionable insights for stakeholders, and with a focus on explainability where AI is used.
Actively influence and shape Finance AI capability development, including vision, strategy & roadmap.
Required Qualifications
Bachelors degree in Data Science, Business Analytics, Finance, Economics, or equivalent experience required. Experience will be evaluated based on the Core Competencies for the role (e.g. extracurricular leadership roles, military experience, volunteer roles, work experience, etc.)
8+ years experience in financial/business analysis or finance or related field.
Preferred Qualifications
6+ years of applied data science experience, preferably in finance, technology or similar data-rich industries.
Proven FP&A experience including topline forecasting and reporting & analysis.
Strong hands-on experience in using both classical AI/ML and generative/agentic AI & LLMs, and with expertise in Python Data Science stack and deep learning frameworks.
Predictive expertise using AI/ML techniques & time-series models, simulation & optimization. Able to innovate, influence & drive buildouts of custom forecasting models & approaches.
Proficiency in Python or other similar programming languages and SQL, including data manipulation, workflows, data science & predictive modeling and forecasting stack.
Able to influence and drive feature engineering based on business drivers and available data enrichment options to maximize AI accuracy.
Take a first-principles based approach to influence implementations and continuously improve AI accuracy as LLMs/AI tools & techniques continue to evolve.
Ability to apply insights to high-impact questions with immediate and long-term relevance.
Ability to think creatively, disrupt long-standing views or processes, deal with ambiguity (building from a clean sheet) and quickly adapt & grow.
Operate with a sense of urgency and be able to iterative towards a solution.
Experience driving data readiness, including cleaning, aggregating, and pre-processing large granular datasets from varied sources including structured & unstructured data.
Excellent verbal and written verbal communication skills, with the ability convey black-box financial outputs from AI to non-technical stakeholders.
This role is hybrid and goes into the office 3 days per week.