Senior Business Operations Analyst

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Who we are:

Shape a brighter financial future with us.

Together with our members, we’re changing the way people think about and interact with personal finance.

We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way.

Join us to invest in yourself, your career, and the financial world.

About the Role

We’re looking for a Senior Data Analyst to join the Business Intelligence team supporting Operations at SoFi. In this role, you will be the analytical engine supporting various Operations functions and initiatives, translating complex operational data into the insights and narratives that drive performance, service quality, and member experience.

This role sits within a broader data organization and supports stakeholders across Frontline and Backline Operations Teams, Workforce Management, and Customer Experience teams. You will help operational leaders better understand performance and identify bottlenecks by architecting comprehensive reporting frameworks and performing deep-dive diagnostic analyses to uncover the 'why' behind our metrics.

You will work across a diverse spectrum of operational datasets—including omnichannel contact data, IVR and chatbot interactions, customer experience (CX) sentiment metrics, and agent productivity performance.

This is a strong fit for someone who thrives at sitting in the intersection of business operations and data analytics. You have a talent for building deep partnerships to understand operational needs, a passion for building reporting and analytical frameworks from the ground up, and a track record of leveraging modern AI tools to work faster and smarter to pave the strategic roadmap for our Operations team.

What You’ll Do

• Serve as a thought partner to leadership — helping define what operational excellence looks like through data.
• Act as a reporting leader for Operations, setting standards for how SoFi measures, monitors, and improves the member experience through data.
• Own and drive reporting roadmaps, ensuring consistency, data accuracy, and scalability.
• Partner with Operations and CX leaders to define, monitor, and evolve key performance indicators (KPIs) that align with service excellence and business objectives.
• Lead the design, automation, and maintenance of Tableau reporting suite for Operations stakeholders, establishing a scalable 'source of truth' for operational performance and member experience metrics.
• Partner with Data Engineering to define business logic and data requirements, ensuring that upstream data collection is structured to support accurate, scalable downstream analytics.
• Develop reporting frameworks that unify data from multiple sources ( ex. customer experience metrics, contact center systems, agent productivity tracking, workforce management, and survey tools
• ) into cohesive, actionable insights.
• Lead deep-dive diagnostic analyses—including variance and root cause investigations—to uncover performance drivers and identify opportunities to reduce member friction or operational inefficiency.
• Leverage cutting-edge AI tools (such as Claude, Cursor, ChatGPT, and AI coding assistants) to accelerate analytical workflows, automate query/script building, and deliver faster, smarter insights.
• Proactively identify emerging trends and 'unknown unknowns' within operational data to alert leadership of risks or opportunities before they impact member experience or SLAs.
• Translate analytical findings into strategic recommendations that influence process design, workforce planning, and continuous improvement initiatives.
• Lead data storytelling efforts, ensuring insights are communicated clearly and persuasively to both technical and non-technical audiences.
• Collaborate with Product, Engineering, Data Science, and other BI teams to enhance data accessibility and automate recurring analytics.
• Mentor junior analysts and cross-functional partners on best practices for data-driven performance management, visualization, and AI-assisted analytics.

What You’ll Need

Bachelor’s degree in Analytics, Statistics, Economics, Engineering, or a related quantitative field (Master’s preferred).

5+ years of experience in data analytics, operations analytics, or business intelligence—ideally within a high-growth FinTech or regulated financial environment.

Proven experience analyzing complex operational datasets, such as contact data, customer experience data, and agent productivity metrics.

Advanced SQL skills with the ability to write complex, performant queries to extract insights from large-scale data warehouses.

Advanced proficiency in Tableau

(highly preferred) or other visualization tools (Looker, Power BI) to build scalable, automated dashboarding suites.

Demonstrated ability to be on the leading edge of modern AI analytics tools (e.g., Claude, Cursor, ChatGPT) to optimize workflows, code more efficiently, and deliver impactful insights faster.

Proven track record of “building from the ground up”—specifically designing new reporting frameworks, defining KPIs, and establishing data "sources of truth."

Elite communication and storytelling skills, with the ability to simplify complex data and influence non-technical stakeholders and leadership.

Strong business acumen and a passion for improving member experiences through data-driven decision-making.

Comfort navigating ambiguity and working in fast-paced environments with evolving priorities and cross-functional dependencies.

Nice to Have

Experience in business banking, commercial banking, or fintech with an understanding of lending, payments, or risk operations.

Familiarity with operational performance management, workforce planning, service operations, risk operations, or process optimization.

Experience working in regulated environments with attention to governance, controls, and auditability.

Familiarity with Python, R, or other analytical tools.