Sr. Analyst, Customer Analytics

Subway•Miami, FL

About The Position

The Senior Analyst, Customer Analytics drives customer and loyalty analytics across Subway’s digital ecosystem. Partnering with product, marketing, loyalty, IT, and analytics, this role turns guest behavior, loyalty performance, and campaign outcomes into insights that lift acquisition, engagement, conversion, retention, and revenue.You will analyze behavior across digital touchpoints, measure loyalty and CRM effectiveness, build audience segments, and map KPIs across the customer journey. Strong SQL skills and experience with modern cloud platforms (Redshift, Snowflake, Databricks) and BI tools (Tableau, Power BI) are essential. This is a high-visibility, cross-functional role with regular exposure to VP- and executive-level leaders.

Requirements

Bachelor’s degree in analytics, statistics, economics, marketing, business, computer science, or a related field.
5–7 years in customer, loyalty, CRM, or digital analytics.
Strong SQL with hands-on experience querying large datasets.
Experience with cloud data platforms such as Redshift, Snowflake, or Databricks.
Proficiency in Tableau and/or Power BI.
Proven work analyzing customer behavior, segmentation, lifecycle, loyalty, and campaign performance.
Solid grasp of KPI development and customer journey measurement.
Cross-functional experience with product, marketing, loyalty/CRM, and technology teams.
Strong communicator who translates analysis into business recommendations for senior stakeholders.

Nice To Haves

Adobe Experience Platform (RTCDP, AJO, CJA).
Experimentation, personalization measurement, and audience-based decisioning.
CRM, lifecycle marketing, or loyalty program support.
Python, R, or similar analytical languages.
AI/LLM tools applied to analysis, workflow efficiency, or knowledge management.
QSR, retail, ecommerce, or other high-volume transactional environments.

Responsibilities

Analyze guest and member behavior across acquisition, engagement, retention, churn risk, and lifetime value.
Measure loyalty program performance: member growth, frequency, redemption, retention, and incremental impact.
Surface opportunities to improve conversion, repeat purchase, basket size, and engagement across digital touchpoints.
Build segment-level insights to power targeted marketing, product, and loyalty strategies.
Partner with CRM analytics to ensure strategic alignment.
Run cohort, lifecycle, and behavioral segmentation analyses to identify key drivers of guest behavior.
Measure campaign, journey, and offer performance across owned and paid channels.
Identify high-value segments, engagement triggers, and personalization opportunities.
Evaluate offer mechanics, loyalty incentives, and promotional constructs.
Partner with loyalty and marketing on campaign effectiveness, reach, and downstream business impact.
Operationalize an audience-driven analytics agenda spanning messaging, segmentation, personalization, and CX.
Build and refine KPI frameworks linking customer behavior to business outcomes across the guest journey.
Document customer, loyalty, product, and campaign KPIs for consistency, transparency, and actionability.
Translate complex datasets into clear narratives for product, marketing, loyalty, and leadership audiences.
Deliver dashboards, recurring reports, and executive-ready insights.
Support business cases, opportunity sizing, and impact modeling tied to customer and loyalty initiatives.
Write complex SQL to extract, join, validate, and analyze customer and behavioral data.
Work across clickstream, profile, loyalty, campaign, transaction, and audience datasets.
Build scalable reporting in Tableau and Power BI.
Use Adobe Experience Platform (RTCDP, AJO, CJA) for audience, journey, and cross-channel insight generation.
Partner with engineering and data teams on data quality, event mapping, and measurement design.
Apply LLMs and AI-enabled workflows to speed insight generation, documentation, taxonomy, and KPI mapping.
Embed customer insights into product roadmaps, campaigns, and experience decisions.
Present findings and recommendations to senior stakeholders, including VP and executive audiences.
Shift customer analytics from reactive reporting to proactive, decision-driving insight.
Foster a culture of analytical rigor, experimentation, and business-minded storytelling.