JOB DESCRIPTION Overview We are seeking a Manager, Customer Analytics to lead customer segmentation, audience strategy, campaign measurement, and customer insights for a large, data-driven consumer organization. This role will partner closely with Marketing, Loyalty, Personalization, Digital, and Media teams to leverage customer data, optimize marketing performance, and drive business growth. The successful candidate will combine strong analytical expertise with people leadership, helping shape customer strategy, influence business decisions, and lead a team responsible for reporting, experimentation, and advanced customer analysis. Key Responsibilities Customer Segmentation & Insights

• Lead the development of customer and audience segmentation strategies using behavioral, transactional, and demographic data.
• Conduct analyses such as customer lifetime value (LTV), RFM, basket analysis, churn analysis, and customer profiling.
• Translate complex data into actionable insights that improve customer acquisition, retention, loyalty, personalization, and marketing effectiveness.
• Act as a thought leader in understanding customer behavior and identifying opportunities for growth. Campaign Measurement & Analytics
• Partner with Marketing, Loyalty, Personalization, and Media teams to define KPIs, success metrics, and measurement frameworks.
• Evaluate campaign effectiveness across channels including email, digital, web, app, and paid media.
• Design and support experimentation programs, including A/B testing, holdout testing, audience testing, and incrementality measurement.
• Ensure measurement approaches align with business objectives and provide meaningful insights for decision-makers. Reporting & Business Performance
• Develop and maintain dashboards, scorecards, executive reporting, and quarterly business reviews.
• Establish reporting standards, measurement methodologies, and analytics best practices.
• Deliver strategic recommendations that influence marketing investment, customer engagement strategies, and business priorities. Leadership & Stakeholder Management
• Lead, coach, and develop a team of analytics professionals.
• Prioritize work across recurring reporting, strategic initiatives, and ad hoc business requests.
• Partner with stakeholders to manage expectations, align on priorities, and communicate analytical findings effectively. - Simplify technical concepts and analytical methodologies for non-technical audiences while maintaining credibility with highly technical teams.

REQUIRED SKILLS AND EXPERIENCE

• 7+ years of experience in Customer Analytics, Marketing Analytics, Business Intelligence, Data Science, or a related field. - 3+ years of people leadership experience. - Strong hands-on experience building customer segmentation strategies and audience frameworks. - Advanced SQL skills for data extraction, transformation, and analysis. - Experience with dashboarding and visualization tools such as Tableau, Looker, Power BI, or similar platforms. - Proven ability to analyze CRM, loyalty, personalization, eCommerce, or digital marketing programs. - Strong business acumen with the ability to translate analysis into actionable recommendations. - Excellent communication and stakeholder management skills.

NICE TO HAVE SKILLS AND EXPERIENCE

• Experience in retail, eCommerce, consumer, loyalty, or marketing-focused environments. - Knowledge of statistical modeling, predictive analytics, and customer behavior analysis. - Experience with experimentation methodologies including A/B testing, incrementality testing, attribution, or marketing mix modeling. - Experience with Python, R, or other analytical/statistical tools. - Familiarity with cloud-based data platforms and large-scale datasets. - Experience working with marketing automation, CRM, or customer engagement platforms.

Key highlights:

• Strong customer segmentation expertise with the ability to independently build segmentation strategies, define criteria, and explain the rationale behind recommendations—not simply execute business-defined segments. - Solid data science foundation with an understanding of analytics methodologies, modeling concepts, and statistical approaches, even if not performing hands-on data science work. - Excellent communication skills, with the ability to translate complex analytical concepts into clear business insights and tailor messaging for both technical and non-technical audiences. - Confident stakeholder management, capable of presenting methodologies, defending recommendations, and managing expectations in a direct yet collaborative manner. - People leadership and influence, including the ability to effectively partner with a highly technical analytics team and earn credibility with data scientists. - A growth mindset and strong sense of ownership, with someone who is energized by the opportunity to help shape the team's future and drive the vision forward.