Manager, Revenue Forecasting & Analytics

Mountain Digital, Inc.; United States; On-site; USD 120,000 - 160,000; Full time

Job summary

Mountain Digital, Inc. in the United States is seeking a Manager, Revenue Forecasting & Analytics to lead a team responsible for forecasting revenue, spend, and net revenue, and to drive long-range planning.

You will build scalable models, partner across Finance, Revenue, Data, and Engineering, and evolve forecasting platforms from spreadsheets to enterprise planning tools, enabling executive decision-making.

Qualifications

• 8+ years in financial forecasting, analytics, or planning in a SaaS/technology company.
• 4+ years of people management leading analytics teams.
• Deep expertise in revenue, spend, and long-range forecasting for tech businesses.
• Strong SaaS metrics, unit economics, and forecasting methodologies.
• Ability to identify data/process gaps and drive improvements.
• Proven ability to influence cross-functional partners without direct authority.
• Experience with enterprise planning platforms (Adaptive Planning, Anaplan, Pigment).
• SQL skills for data validation and exploration.

Responsibilities

• Lead, coach, and develop a team of Financial Analytics Engineers.
• Own forecasting methodologies across revenue, spend, net revenue, and planning.
• Design and evolve driver-based forecasting models for executive decision-making.
• Identify data gaps and lead cross-functional remediation efforts.
• Influence Finance, Revenue, Operations, Data, and Engineering for process improvements.
• Advance forecasting from spreadsheet-based to scalable planning platforms.
• Partner with Engineering to operationalize forecasting models in data platforms.
• Establish governance and feedback loops to measure forecast performance.

Skills

Forecasting leadership

People management

Forecasting models

SaaS metrics knowledge

Root-cause analysis

Influencing without authority

Enterprise planning platforms

SQL proficiency

Tools

Adaptive Planning

Anaplan

Pigment

Job description

Manager, Revenue Forecasting & Analytics

United States

This role leads the team responsible for building and scaling MNTN's forecasting capabilities. Reporting to the Senior Manager, Business Analytics Engineering, you will own the models, methodologies, and planning processes that drive revenue forecasting, spend forecasting, net revenue projections, and executive scenario planning.

This is not a traditional FP&A role. Rather than owning budgets, accounting, close, or financial reporting, you will own the forecasting function, developing scalable models and planning frameworks that predict the business’s direction.

Success depends on continuously identifying and improving forecast accuracy and timeliness, influencing without direct authority, and partnering across Finance, Revenue, Data, and Engineering.

What You'll Do

• Lead, coach, and develop a team of Financial Analytics Engineers, setting priorities, driving execution, and fostering a high‑performing, accountable culture.
• Own the company's forecasting methodology across revenue, spend, net revenue, and company planning, continuously improving forecast accuracy and consistency.
• Design, build, and evolve driver‑based forecasting models that support executive decision‑making, long‑range planning, and scenario analysis.
• Continuously identify gaps in data, systems, and business processes that limit forecasting accuracy or scalability, and lead cross‑functional efforts to resolve them.
• Influence stakeholders across Finance, Revenue, Operations, Data, and Engineering to implement process improvements, improve data quality, and strengthen the systems that power forecasting.
• Lead the evolution of forecasting from spreadsheet‑driven processes to scalable planning platforms and repeatable workflows.
• Partner with Engineering to operationalize forecasting models within modern data platforms and planning tools.
• Establish governance, documentation, and feedback loops that measure forecast performance, identify root causes of variance, and drive continuous improvement.

What You'll Bring

• 8+ years of experience in financial forecasting, strategic finance, financial analytics, or business planning within a modern SaaS, fintech, advertising technology, or other high‑growth technology company.
• 4+ years of people management experience, with a proven track record of building, coaching, and developing high‑performing technical or analytics teams.
• Deep expertise building forecasting models for revenue, spend, net revenue, and long‑range planning in a technology business.
• Strong understanding of SaaS and technology business metrics, unit economics, financial statements, and forecasting methodologies.
• Demonstrated ability to identify root causes behind forecasting or planning challenges and drive improvements to business processes, systems, or data quality.
• Proven success influencing cross‑functional stakeholders without direct authority to implement operational or technical change.
• Experience with enterprise planning platforms such as Adaptive Planning, Anaplan, Pigment, or similar forecasting tools.
• Comfortable using SQL to validate and explore data; deep analytics engineering expertise is not required.

What Success Looks Like

• Forecast accuracy improves because you systematically identified and resolved the underlying data, process, and systems gaps – not just refined forecasting models.
• Revenue, spend, and company forecasts become trusted inputs for executive decision‑making because assumptions are transparent, methodologies are consistent, and business inputs are reliable.
• Cross‑functional teams adopt new processes and system improvements that strengthen the quality, consistency, and timeliness of forecasting inputs.
• Forecasting evolves from a spreadsheet‑driven exercise into a scalable planning capability supported by modern systems, reliable data, and repeatable workflows.
• Your team is recognized as a trusted strategic partner, proactively identifying risks, surfacing opportunities, and driving improvements across Finance, Revenue, Operations, Data, and Engineering.