Senior Analyst, Customer Experience Analytics

Role Summary / Purpose

The Senior Analyst, Customer Experience Analytics role will be responsible for owning analyses that drive measurable improvements in operational performance and customer experience. This role will partner cross‑functionally and work closely with analytic leadership to solve complex problems and enable better strategic decisions on customer engagement. The ability to handle multiple projects at once, thrive in a fast‑paced environment, and effectively communicate to leadership are critical to success in this role.

• Own end‑to‑end analytics delivery: translate business questions into analytic approach, build/validate datasets from disparate sources, perform analysis, and deliver actionable recommendations.
• Lead root‑cause investigations on operational performance shifts (e.g., increases in handle time, contact drivers, etc.).
• Influence adoption: align stakeholders on actions, quantify expected impact, and track realized results post‑implementation.
• Communicate insights effectively: tailor messaging for senior leaders vs. working teams; present assumptions, limitations, and recommended next steps.
• Proactively identify, analyze, and solve business problems with a focus on understanding the root causes.
• Become a subject matter expert for data across multiple clients and warehouses.
• Provide clear timelines, manage multiple parallel requests, and maintain a transparent prioritization approach.
• Perform other duties and/or special projects as assigned.

• Bachelor's degree OR in lieu of a degree, a high school diploma and 3+ years of analytics experience in financial services, credit card and/or payments industries.
• 2+ years of experience in an analytics role with a focus on digital engagement analytics preferred.
• 1+ year of experience with statistical tools such as SAS, SQL, R, or/​and Python.
• Comfortable analyzing large datasets in a warehouse environment.
• Demonstrated ability to translate ambiguous business questions into structured analyses and recommendations.
• Ability and flexibility to travel for business as required.
• OR
• Master’s Degree and:
• At least 1 year of experience in an analytics role in financial services, credit card and/or payments industries.
• 1+ year of experience with statistical tools such as SAS, SQL, R, or/​and Python.
• Comfortable analyzing large datasets in a warehouse environment.
• Demonstrated ability to translate ambiguous business questions into structured analyses and recommendations.
• Ability and flexibility to travel for business as required.

• Bachelor's degree in STEM or related quantitative field.
• Master’s Degree in STEM or related quantitative field.
• Analytics role in financial services, credit card and/or payments industries is strongly preferred.
• SAS experience is preferred.
• Strong written and verbal communication skills; able to tailor messages to technical and non‑technical audiences.
• Experience working with multiple source systems and enterprise data warehouses; comfortable navigating data lineage and definitions.
• Strong data storytelling and visualization skills; able to translate complex analyses into clear insights and recommended actions.
• Proven ability to influence and collaborate across cross‑functional teams without direct authority.
• Working knowledge of common analytics approaches (e.g., trend/variance analysis, segmentation, KPI design, root‑cause analysis, A/B testing).
• Strong organizational and project‑management skills; able to manage multiple priorities independently and meet deadlines.
• Experience structuring and executing complex analyses.
• Comfortable operating in a fast‑paced environment; able to deliver high‑quality ad‑hoc analyses under tight timelines.
• Ability to synthesize diverse inputs into practical recommendations and clearly articulate findings to business partners and senior leaders.
• Proven understanding of the financial services/credit card/payments industry.
• Familiarity with Net Promoter Score (NPS) and customer sentiment analytics, including interpreting feedback trends and translating insights into operational improvements.

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