Senior Financial Analyst (R&D/Customer Success)

With over 30,000 customers, including a third of Fortune 500 companies, Tempo is trusted by organizations across the globe to make their workflows work better.

We create a suite of integrated solutions for time management, resource planning, budget management, roadmapping, program management, reporting and more. We create the tech that enables the modern team to deliver – for every step from first vision to value.

Since our beginning in 2007 as a project to make a time-tracking tool to help a client – Tempo has expanded to become the #1 time management add-on for Jira, and we have developed and acquired a multitude of tools to become one of the most trusted names in the Atlassian ecosystem.

We want everyone to work better – but we also want to be a tech company with a heart. Join us as we continuously innovate our award-winning products, create new solutions, and help the world work smarter, not harder.

About the role:

Tempo is seeking a highly analytical and forward-thinking Senior Financial Analyst to support Product & Engineering (R&D) and Customer organizations while helping build an AI-enabled Finance function.

This role partners directly with the CTO, CPO, and CCO, owning the R&D financial model and supporting Customer forecasting, performance, and operational decision-making. In parallel, this role will play a key part in evolving Finance from a traditional reporting function into a scalable, agent-enabled operating system.

You will design, operationalize, and continuously improve workflows across forecasting, reporting, and analysis—leveraging AI, automation, and agent orchestration to increase speed, accuracy, and insight generation. A critical component of this role is ensuring data integrity across financial and operational systems, including close processes, to enable reliable automation and decision-making.

This role reports to the VP of Finance and operates as a thought partner who challenges assumptions, improves systems, and drives better decisions.

What you’ll do:

R&D & Customer Finance

• Own the R&D financial model (headcount, capacity, investment prioritization)

• Build and/or orchestrate planning cycles (annual plan, reforecasts, weekly flash) across R&D and Customer

• Partner with the CCO on Customer Success and Support forecasting, capacity, and performance

• Deliver insights on core SaaS metrics (retention, churn, expansion, cost-to-serve, support efficiency)

• Inform topline assumptions based on customer behavior, product usage, and operational drivers

• Support quarterly business reviews and development of board-level materials

Cloud Cost & Strategic Analysis

• Partner with Cloud Operations to forecast and manage cloud and AI costs

• Drive visibility into cost drivers and identify efficiency opportunities

• Build and/or orchestrate business cases, scenarios, and sensitivity analyses

• Act as a strategic thought partner to R&D and Customer leadership on resource allocation and ROI

AI, Agents & Workflow Orchestration

• Design, build, and orchestrate AI-driven workflows across forecasting, reporting, and variance analysis

• Translate finance processes into structured, modular workflows for agent execution

• Orchestrate multi-step, agent-driven processes across interconnected workflows

• Act as human-in-the-loop owner (output validation, exception handling, continuous improvement)

• Replace manual processes with orchestrated agent workflows to scale output without linear headcount

• Integrate data pipelines with AI and orchestration layers (Finance Systems, BI, RevOps, Accounting, HR, etc.)

• Continuously improve workflows through prompt refinement and orchestration optimization

Close Partnership & Data Integrity

• Partner with Accounting to ensure accurate expense classification and allocations during close

• Align financial data with operational drivers (headcount, cloud usage, vendor spend)

• Build and/or orchestrate accruals, reclasses, and variance explanations

• Establish and enforce data governance and documentation standards across systems

• Ensure data structures are clean, consistent, and automation-ready for AI workflows

• Identify and resolve data issues impacting forecasting, reporting, or automation accuracy

Reporting & Operational Excellence

• Deliver monthly reporting, variance analysis, and performance insights

• Support weekly, monthly, an