Senior Financial Analyst, GTM

Luxury Presence

1d•$110,000 - $140,000•Remote

About The Position

This role sits at the intersection of data and finance. You will be the analytical engine behind our go-to-market decisions, partnering with Sales, CS, Marketing, and Revenue Operations to forecast the business, model go-to-market efficiency, and turn data warehouse queries into insight that shapes where we invest. The ideal person has lived in both worlds, a data or analytics role and a finance or FP&A role, and moves comfortably between a SQL query and a financial model. This is a role for someone who likes hard problems, is genuinely curious about how Sales and CS drive growth, and wants their analysis to shape real decisions.

Requirements

4+ years spanning both a data or analytics role and a finance or FP&A role, ideally at a high-growth SaaS or technology company.
Hands-on experience with go-to-market or SaaS metrics: pipeline, bookings, ARR, CAC, LTV, payback, and sales efficiency.
Expert in SQL, comfortable working directly in a data warehouse to build and validate datasets.
Advanced Excel and strong financial modeling, budgeting, and forecasting.
Bachelor's degree in Finance, Accounting, Economics, Statistics, or a related quantitative field.
Excellent analytical, problem-solving, and communication skills.
Fluent in both data and finance, comfortable moving between a SQL query and a financial model.
Genuinely curious about go-to-market and how sales and marketing drive growth.
Execution-oriented, with a strong sense of ownership over accuracy and deadlines.
AI-forward, always looking for ways to automate and sharpen the work.

Responsibilities

Own the Sales, Marketing and CS annual and long term planning across revenue, staffing and resourcing.
Work closely with Sales, Marketing, CS and Analytics to align go-to-market spend and targets with the financial plan, and to model ongoing investment decisions.
Build and maintain models for CAC, LTV, payback, and sales and CS capacity and productivity, and use them to recommend where go-to-market spend should go.
Query the data warehouse directly to build datasets, validate numbers, and answer questions that mix financial and operational data.
Automate recurring GTM reporting to speed the path from data to decision.