Senior Business Operations Analyst

SoFi•Jacksonville, FL

About The Position

SoFi is seeking a Senior Data Analyst to join its Business Intelligence team supporting Operations. The role translates complex operational data into insights and narratives that help improve performance, service quality, and member experience. It supports stakeholders across Frontline and Backline Operations, Workforce Management, and Customer Experience teams, working with data such as omnichannel contacts, IVR and chatbot interactions, customer experience sentiment, and agent productivity. The analyst partners with operational leaders to define performance measures, build reporting frameworks, and conduct diagnostic analyses that reveal the causes of results and identify improvement opportunities. The role leads the development and maintenance of Tableau reporting, collaborates with Data Engineering on business logic and data requirements, and uses modern AI tools to accelerate analytical workflows. It also communicates recommendations to technical and non-technical audiences and mentors junior analysts and cross-functional partners.

Requirements

Bachelor’s degree in Analytics, Statistics, Economics, Engineering, or a related quantitative field.
At least 5 years of experience in data analytics, operations analytics, or business intelligence.
Experience analyzing complex operational datasets, such as contact data, customer experience data, and agent productivity metrics.
Advanced SQL skills, including writing complex, performant queries for large-scale data warehouses.
Advanced proficiency in Tableau or another visualization tool such as Looker or Power BI.
Experience using modern AI analytics tools such as Claude, Cursor, or ChatGPT to optimize workflows and deliver insights.
Experience designing reporting frameworks, defining KPIs, and establishing data sources of truth.
Strong communication and data storytelling skills, including the ability to simplify complex data and influence non-technical stakeholders and leadership.
Strong business acumen and interest in improving member experiences through data-driven decision-making.
Ability to navigate ambiguity and work in fast-paced environments with evolving priorities and cross-functional dependencies.

Nice To Haves

Master’s degree.
Experience in high-growth FinTech or a regulated financial environment.
Experience in business banking, commercial banking, or fintech, with understanding of lending, payments, or risk operations.
Familiarity with operational performance management, workforce planning, service operations, risk operations, or process optimization.
Experience in regulated environments with attention to governance, controls, and auditability.
Familiarity with Python, R, or other analytical tools.

Responsibilities

Serve as a thought partner to leadership, using data to help define operational excellence.
Set standards for how Operations measures, monitors, and improves 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 KPIs aligned with service excellence and business objectives.
Design, automate, and maintain Tableau reporting for Operations stakeholders as a scalable source of truth for operational performance and member experience metrics.
Partner with Data Engineering to define business logic and data requirements for accurate, scalable downstream analytics.
Develop reporting frameworks that combine customer experience, contact center, agent productivity, workforce management, and survey data.
Lead variance and root-cause analyses to uncover performance drivers and opportunities to reduce member friction and operational inefficiency.
Use AI tools to accelerate analytical workflows, automate query and script building, and deliver insights more efficiently.
Identify emerging trends and unexpected risks or opportunities in operational data before they affect member experience or SLAs.
Translate analytical findings into recommendations that inform process design, workforce planning, and continuous improvement.
Communicate insights clearly and persuasively to technical and non-technical audiences.
Collaborate with Product, Engineering, Data Science, and BI teams to improve data accessibility and automate recurring analytics.
Mentor junior analysts and cross-functional partners in data-driven performance management, visualization, and AI-assisted analytics.