Data Analyst, Macro Analytics

About Stripe

Stripe serves as a financial infrastructure platform supporting a wide range of companies, from large enterprises to ambitious startups, enabling them to process payments, expand revenue, and accelerate business growth. Their mission is to boost the internet's GDP, presenting outstanding opportunities to influence the global economy positively.

About the Team

The Data Science group at Stripe is an active community comprising data analysts, scientists, and engineers who collaborate to handle Stripe’s core data. Various Data Analytics roles exist across the company, and candidates are placed in teams best suited to their experience.

Role Overview and Responsibilities

• Collaborate with Treasury Finance, Finance & Strategy, Risk, and Engineering teams to develop analytics and observability frameworks regarding Stripe's financial health
• Conduct analysis of macroeconomic indicators to build frameworks that guide financial planning and strategic decision-making
• Create targeted performance and observability analytics for both standard and event-driven settings, providing senior leaders insights on Stripe’s business amid changing macro/market conditions
• Utilize Stripe’s data assets to evaluate financial outcomes and create scalable data architectures to support current and emerging analyses
• Work with varied and non-standard data to extract actionable insights and recommendations
• Coordinate with data scientists and engineers to construct data pipelines, models, and infrastructure aligned with business goals
• Maintain ongoing reporting, fulfill stakeholder communication needs, and respond to information requests within Treasury Finance and Finance & Strategy

Candidate Profile

Applicants should meet the essential criteria below. Preferred qualifications enhance candidacy but are not required.

Minimum Requirements

• Residence within New York City or willingness to relocate, as the role involves hybrid work
• 3 to 6 years of experience in data research and analysis, risk modeling, business intelligence, or data engineering, including data pipeline development and large dataset analysis
• Strong proficiency in SQL and Python programming languages
• Deep understanding of statistics coupled with good business sense
• Effective communication skills to clearly present findings and drive business impact
• Experience in analytics within FinTech, banking, investment management, corporate finance, treasury, or financial services sectors
• Expertise in data visualization and leveraging insights to inform decision-making and objectives
• Demonstrated ability to manage multiple projects simultaneously with careful attention to detail
• Capability to collaborate cross-functionally to identify challenges in data analytics and deliver rigorous, data-driven solutions
• Proficiency in using AI tools to expedite model development, data analysis, and coding tasks

Preferred Qualifications

• Master’s degree in Mathematics, Statistics, Economics, Engineering, or related technical field
• Experience at a fast-growing internet or FinTech firm
• Background in macro analytics, corporate finance, financial planning, or portfolio management
• Familiarity with financial and accounting data, time-series analyses, macroeconomic studies, or development of economic indicators
• Experience handling distributed data frameworks such as Hadoop and Spark for building and troubleshooting data pipelines
• Understanding of software development best practices including engineering standards, code review, and testing protocols

Work Environment

Employees assigned an office location are generally expected to spend at least half of their working days per month in the office or engaging with users. This may differ by role and team, with certain locations requiring full-time in-office presence. Some teams may call for more frequent in-person attendance to enhance collaboration, a topic managed by the hiring manager.

Compensation and Benefits

The base salary range for this position in the US is $134,000 to $201,000 annually, covering various seniority levels and adjusted within interviews by experience and location. Additional compensation may include stock equity, company bonuses, or sales commissions, along with benefits like 401(k), medical, dental, vision coverage, and wellness allowances.