Senior Data Scientist, Finance

Data at Brex

Our Scientists and Engineers work together to make data — and insights derived from data — a core asset across Brex. But it's more than just crunching numbers. The Data team at Brex develops infrastructure, statistical models, and products using data. Our work is ingrained in Brex's decision-making process, the efficiency of our operations, our risk management policies, and the unparalleled experience we provide our customers.

What You’ll Do
Working closely with Finance leadership, you’ll develop a financial forecasting system using advanced data science techniques. You’ll analyze key business drivers to inform strategic financial decisions and enhance forecast precision. The ideal candidate has expertise in predictive modeling, causal inference, and experience collaborating with Corporate and Strategic Finance teams, particularly in forecasting within a blended revenue model that includes both recurring and consumption-based components.

Where you’ll work

This role will be based in our New York office. You must be willing to work in office at least 2 days per week on Wednesday and Thursday. Employees will be able to work remotely for up to 4 weeks per year.

Responsibilities:

• Design and build a new top-line revenue and other financial forecasts using predictive modeling and other advanced data science techniques. 
• Collaborate with Finance to integrate predictive insights into existing forecasting processes and refine key assumptions.
• Partner with Finance to analyze financial performance and uncover key drivers using causal inference, anomaly detection, and exploratory data analysis.
• Design and implement scalable data pipelines to support financial reporting and forecasting in collaboration with Data Engineering.
• Mentor junior data scientists and finance analysts to foster a culture of data-driven decision-making.
• Communicate findings and recommendations clearly to both technical and non-technical audiences.

Requirements:

• Master's degree or Ph.D. in Finance, Statistics, Economics or a related quantitative field.
• 5+ years of experience in a data science or related role supporting finance teams.
• Expertise in predictive modeling, causal inference, and time series forecasting.
• Knowledge of structural finance models, financial planning and analysis (FP&A) workflows and reporting, plus experience working with key performance indicators like LTV, CAC, and ARR.
• Proficiency in SQL and Python (or R) for data analysis and modeling.
• Ability to translate complex analyses into strategic recommendations for Finance and business leadership.
• Familiarity with BI tools (e.g., Tableau, Looker) and financial data sources.
• Excellent problem-solving skills and the ability to work independently in a fast-paced environment.
• Strong communication skills, with the ability to work cross-functionally.

Bonus Points:

• Experience building and maintaining financial forecasting models with a high degree of accuracy.
• Experience working in businesses with blended revenue models that include both recurring and consumption-based components.

Compensation

The expected salary range for this role is $192,000 - $240,000. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.