Senior Business Analytics Manager

Job Requisition ID # 26WD99697 Position Overview We are seeking a Senior Business Analytics Manager to support Go-to-Market Finance organization by driving data-informed strategy, building scalable analytics solutions and AI-enabled workflows that improve planning, forecasting and reporting. This role will play a critical part in accelerating time to insights, reducing manual work, and shaping how Finance uses data, automation, and AI to make better business decisions. As a manager in the Business Analytics function, you will lead a team responsible for complex, cross-functional initiatives across Finance, Sales, Data Engineering, and business operations. You will translate ambiguous business problems into structured analytical frameworks, scalable data products, and practical AI-enabled solutions that improve decision quality and operational efficiency. The ideal candidate can operate at both the strategic and executional level: partnering with senior stakeholders to define the right business problems, while also being hands-on enough to query data, prototype solutions, pressure-test metrics, and partner with technical teams to scale durable products. This is a senior individual contributor role that requires strong business judgment, technical depth, product thinking, and the ability to influence and scale solutions across teams. Responsibilities Lead end-to-end analytics and AI-enabled workflow initiatives, from problem framing and stakeholder alignment to solution design, insight generation, adoption, and measurable business impact Partner closely with Finance stakeholders to understand planning, forecasting and reporting workflows, and identify opportunities to improve them through data, automation, and AI Translate ambiguous Finance and business challenges into structured analytical frameworks, including data modeling, KPI design, forecasting, experimentation, and decision-support workflows Design and build scalable data products, including pipelines, tables, dashboards, reporting layers, and AI-ready datasets that enable automated, flexible, and action-oriented Finance analytics Build and test prototypes for AI-enabled Finance workflows, such as automated business review narratives, anomaly detection, variance explanation, forecast drivers, natural-language insight discovery, and self-service reporting Partner with Data Engineering, Finance Systems and central data teams to move prototypes into reliable, governed, production-ready solutions Define and standardize KPI frameworks for financial metrics ensuring alignment across Finance and business teams Design and scale dashboards, reporting solutions, and self-service analytics experiences that improve adoption, reduce manual reporting, and help business partners make faster, more consistent decisions Analyze business and financial metrics to uncover key drivers of growth, retention, churn, productivity, and efficiency, and recommend clear data-backed actions Establish scalable, repeatable analytics frameworks and best practices that improve Finance decision-making and create consistency across planning, forecasting, reporting, and business reviews Apply strong governance, quality control, and documentation practices to ensure AI-enabled workflows are accurate, explainable, secure, and appropriate for Finance decision support Communicate insights, recommendations, and roadmap tradeoffs to senior leadership through clear storytelling, executive-ready presentations, and concise written narratives Manage, coach, and develop analysts and contribute to raising the overall analytical, technical, and AI-readiness capabilities of the Business Analytics team Minimum Qualifications Bachelor’s degree or higher in a quantitative field 8-10+ years of experience in analytical fields such as consulting, strategic finance, BizOps, data science, business intelligence, data engineering Advanced SQL skills with the ability to work with large, complex datasets and multiple data sources Strong experience with BI and visualization tools such as Power BI, or similar platforms Experience partnering with Finance, GTM, or business leadership teams to support planning, forecasting, reporting, and performance management Demonstrated ability to structure ambiguous problems, perform deep analysis, and translate findings into clear business impact Experience designing scalable dashboards, reporting solutions, data models, or analytics products that improve self-service and reduce manual work Strong stakeholder management skills, with experience influencing senior business partners and driving alignment across cross-functional teams Excellent communication skills, with the ability to distill complex analysis, technical concepts, and business tradeoffs into clear, actionable recommendations Proven ability to manage analysts, lead cross-functional initiatives and deliver results in a matrixed environment Preferred Qualifications Experience supporting Go To Market, SaaS, or subscription-based business models Experience building analytics, automation, or AI-enabled workflows for Finance, FP&A, GTM Finance, Sales Finance, or business operations teams Experience with Python or other statistical tools for advanced analytics, modeling, or experimentation Experience applying AI, machine learning, or generative AI capabilities to business workflows, such as automated narratives, anomaly detection, forecasting, natural-language analytics, document intelligence, or decision-support tools Experience designing AI-ready data products, semantic layers, metric stores, or governed datasets that support self-service analytics and workflow automation Experience building and deploying predictive models to forecast key metrics Experience designing an optimal decision support process, defining a product strategy to enable it, translating into a roadmap, and enabling it through technology Domain experience in FP&A and / or sales, marketing, and customer success operations Experience working in high-growth or transformation environments Strong understanding of responsible AI practices, including data quality, human-in-the-loop review, model limitations, explainability, and governance considerations Learn More About Autodesk Welcome to Autodesk! 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