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Senior Data Scientist, Finance at Brex Inc.

Brex Inc. No longer available

Job Description

Senior Data Scientist, Finance San Francisco, California, United StatesSenior Data Scientist, Finance Why join us Brex is the AI-powered spend platform. We help companies spend with confidence with integrated corporate cards, banking, and global payments, plus intuitive software for travel and expenses. Tens of thousands of companies from startups to enterprises - including DoorDash, Flexport, and Compass - use Brex to proactively control spend, reduce costs, and increase efficiency on a global scale.Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We're committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. 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 San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of two coordinated days in the office per week, Wednesday and Thursday. Starting February 2, 2026, we will require three days per week in office - Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work! 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 revenue prediction models with demonstrated accuracy in production environments. 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. Please be aware, job-seekers may be at risk of targeting by malicious actors looking for personal data. Brex recruiters will only reach out via LinkedIn or email with a domain. Any outreach claiming to be from Brex via other sources should be ignored.

Typical senior pay: $156k for Data Scientists nationally

National salary averages
Expected senior-level
$156k
Entry
Mid
Senior
Expected
$64k Market range (10th-90th percentile) $194k

Top performers earn significantly more—skill and negotiation matter.

Senior roles pay 89% more than entry—experience is well rewarded.

Strong candidate leverage

High demand and responsive wages. Negotiate confidently on all fronts.

Hiring leverage
Candidate-favored
Wage leverage
Moderate
Mobility
Good mobility

Who this leverage applies to

Stronger for: All experience levels

Where to negotiate

Base salary
Sign-on bonus
Title / level
Remote flexibility
Scope & responsibility
Start date / PTO

Likely Possible Unlikely

Use competing offers and timing to your advantage.

Does this path compound?

Job Growth →
High churn
Growth, flat pay
🚀 Compound
Growth + pay upside
⚠️ Plateau
Limited growth
Specialize
Experts earn more
Pay Upside →
Growth + pay upside

Both the field and your earnings can grow significantly.

+34%
10yr growth
New positions are being created faster than they're being filled.
A bachelor's degree is typically expected.
Typical: Bachelor's degree

Good time to build expertise—demand will chase supply.

Labor data: BLS 2024