Senior Analyst

Overview

This role is with a financial technology organization focused on reinventing credit to provide consumers with transparent, flexible buy now, pay later options without hidden fees or compounding interest. The Risk & Analytics team plays a critical role in shaping business strategy by partnering with Machine Learning, Product, Engineering, Capital Markets, and Commercial teams to optimize approval rates, conversion, losses, and profitability.

The team operates across the entire customer and merchant lifecycle, addressing challenges such as checkout conversion optimization, fraud risk mitigation, scalable data infrastructure, and international expansion. The team builds tools, analytical frameworks, and scalable data foundations to drive efficient and intelligent growth.

Responsibilities

• Own the full analytical lifecycle from initial question to final business decision with autonomy.
• Use advanced data analytics to derive insights and optimize business, risk, or growth strategies across products and geographies.
• Monitor portfolio performance and macroeconomic trends to proactively adjust strategies mitigating risk and balancing growth.
• Collaborate with Engineering and Machine Learning teams to design, build, and interpret performance metrics for scalable risk, fraud, or growth models.
• Work closely with Product, Legal, and Compliance teams to interpret regulatory and market requirements and translate them into analytical policy and product recommendations.
• Oversee development and execution of analytical frameworks, ensuring new product launches and market entries align with risk appetite, operational capabilities, and regulations.
• Engage with external stakeholders such as merchants, vendors, and partners to ensure compliance and strengthen strategic relationships.
• Develop repeatable AI-assisted workflows to enhance team analyses and mentor junior analysts on technical skills and domain knowledge.

Requirements

• 2–5 years of experience in an analytically-driven role within consumer lending, credit, or fintech industries.
• Degree in Data Science, Computer Science, Engineering, Economics, or a related quantitative field.
• Advanced proficiency in SQL, Python, or other scripting languages.
• Expertise in data mining, data visualization, and statistical modeling, including applying machine learning techniques to business or risk management problems.
• Proven experience leading cross-functional initiatives involving Product, Legal, Compliance, and Engineering teams.
• Strong understanding of consumer lending regulations, regional market dynamics, and economic factors influencing policy and growth.
• Ability to translate complex regulatory and economic insights into actionable business strategies.
• Excellent communication skills with the ability to influence senior stakeholders across technical and non-technical teams.

Preferred Qualifications

• Deep domain expertise in consumer finance analytics.
• Experience working in ambiguous environments balancing growth and resilience.
• Demonstrated leadership in cross-functional collaboration and mentorship.

Compensation & Benefits

• Pay Grade: K
• Equity Grade: 6
• Base pay range for CA, WA, NY, NJ, CT: $145,000 - $205,000 per year
• Base pay range for other U.S. states: $128,000 - $188,000 per year
• Total compensation package may include monthly stipends for health, wellness, and technology spending.
• Benefits include 100% subsidized medical coverage, dental and vision for employees and dependents.
• Eligibility for equity rewards.
• Competitive vacation and holiday schedules.
• Employee stock purchase plan allowing discounted share purchases.

Location

• Remote-first company with most roles allowing work from almost anywhere within the country of employment.
• Some roles may require occasional work from assigned offices depending on job responsibilities.

Additional Information

• The organization is committed to providing an inclusive interview experience and reasonable accommodations for candidates with disabilities.
• For U.S. positions potentially based in Los Angeles or San Francisco, qualified applicants with arrest and conviction records will be considered in accordance with local fair chance hiring ordinances.