Senior Manager, Loyalty, CRM & Personalization Analytics

Chipotle•Newport, RI

5d•$150,000 - $222,000•Hybrid

About The Position

The Senior Manager, Loyalty, CRM & Personalization Analytics leads the strategy, execution, and measurement of analytics across Loyalty, CRM, and Personalization. This role translates customer data into decisions that improve lifecycle engagement, campaign performance, personalization effectiveness, and long-term customer value. This is a high-visibility, executive-facing role. The Senior Manager will independently represent Loyalty, CRM, and Personalization analytics in senior leadership and ELT-level discussions, turning complex customer and campaign performance into clear recommendations and business decisions. The ideal candidate is an expert storyteller and strategic problem framer, with the ability to turn ambiguous business questions into clear opportunities, measurable value, and action. Sitting at the center of Loyalty & CRM, Marketing, Digital, Product, Finance, and Data & Analytics, this leader will help improve how performance is measured, how insights are communicated, and how customer growth opportunities are prioritized. The role leads a team of analysts and sets the standard for analytical quality, experimentation rigor, stakeholder engagement, and insight communication.

Requirements

Bachelor’s degree required in Analytics, Statistics, Economics, Engineering, Computer Science, Marketing Science, or a related quantitative field preferred.
10+ years of experience in analytics, strategy, or consulting, with a focus on loyalty, CRM, personalization, lifecycle marketing, or customer growth.
Experience leading, coaching, and developing analytics teams.
Demonstrated success driving measurable business impact in analytically rigorous or high-performance environments.
Strong executive presence, with the ability to lead senior-level discussions, defend recommendations, and influence decisions with clarity and sound business judgment.
Deep experience with customer segmentation, LTV modeling, lifecycle analysis, experimentation, uplift and incrementality measurement, and foundational causal inference.
Hands-on experience with SQL and Python or R, including work with large-scale datasets, modern data platforms such as Snowflake, and BI tools such as Power BI.
Demonstrated ability to synthesize complex analysis into compelling executive narratives that clarify what changed, why it matters, what action is needed, and what business value is at stake.
Strong understanding of campaign analytics, performance measurement, test design, and customer lifecycle reporting.

Nice To Haves

Advanced degree preferred.
Familiarity with CDPs, CRM or ESP platforms, loyalty systems, automation, or AI-enabled analytics tools.
Experience in QSR, restaurant, retail, or other high-frequency consumer businesses with strong lifecycle, loyalty, or digital engagement dynamics.

Responsibilities

Lead the analytics roadmap for Loyalty, CRM, and Personalization, aligning priorities to lifecycle growth, business impact, urgency, and feasibility.
Serve as the primary analytics voice in senior leadership and ELT-level forums, shaping decisions with objective insights and clear recommendations.
Act as an internal consultant and strategic partner by turning ambiguous business questions into clear learning agendas, measurable opportunities, and objective recommendations.
Own measurement and performance management across Loyalty, CRM, and Personalization, including reporting, recurring readouts, and executive-ready narratives.
Build customer cohorts, lifecycle frameworks, and value segmentation to explain performance drivers and surface growth opportunities.
Lead experimentation strategy, including test design, governance, incrementality, uplift measurement, attribution, and performance evaluation.
Ensure consistent, trusted measurement methodologies across reporting, experimentation, and strategic analysis.
Lead, coach, and develop a high-performing team of analysts.
Establish standards for analytical quality, experimentation rigor, stakeholder engagement, and insight communication.
Improve the speed and quality of analytics through better workflows, modern tools, automation, and AI-enabled approaches where they improve the work.
Foster a culture of curiosity, experimentation, collaboration, accountability, and continuous improvement.