Director, Lead Product Data Analyst - Digital

Digital products play a central role in how we create value for customers, support the teams who serve them, and shape the consumer experience. Our product organization brings together small, empowered teams that move with clarity, speed, and purpose, making digital a meaningful source of advantage across our operating unit.

Our work spans the experiences that keep the business running, including customer journeys, service delivery, sales workflows, and the systems that connect them. If you are energized by solving real customer problems, partnering across functions, and shaping products that deliver measurable impact, this role is for you.

About the Role

We are hiring a Lead Product Data Analyst to join our Digital Product Data & Analytics team within the North America Digital & Data organization. Reporting to the Head of Product Data & Analytics, you will join a team of product data analysts and data scientists embedded within empowered, cross-functional squads that partner closely alongside Product, Design, Engineering, Research, and business stakeholders.

In this role, you will help define product outcomes, develop and test hypotheses, and influence prioritization and trade-off decisions across the product roadmap. You will operate with a high degree of autonomy in complex and ambiguous problem spaces. Beyond delivering analyses, you will play a critical role in building the discipline of product analytics by bringing advanced methods, strong product thinking, and creative problem-solving to the enterprise.

This role is a strong fit for an analyst who enjoys working closely with product teams, is curious about how users behave, and is motivated by helping teams learn faster and make better decisions.

What You'll Do

Product Analytics & Experimentation:

• Define and evolve product measurement strategies and success metrics across adoption, engagement, retention, product health, and value creation.

• Analyze product usage, funnels, customer journeys, and segments to uncover user behaviors, friction points, trends, and opportunities that inform product strategy and iteration.

• Apply advanced analytics, statistical methods, and experimentation, including A/B testing, incrementality testing, and quasi-experimental analysis, to understand product performance and quantify impact.

• Partner with Product, Design, Engineering, Data, Commercial, and Operations to translate insights into product strategy, priorities, and action.

• Develop scalable measurement frameworks, playbooks, and experimentation standards that strengthen analytical maturity and outcome-based decision-making across teams.

Instrumentation & Data Quality:

• Define and improve product instrumentation, event tracking, and data structures that accurately reflect user behavior and support product measurement.

• Partner with Application Engineering to implement and validate event instrumentation, ensuring product interactions are captured accurately and consistently.

• Partner with Data Architecture and Data Engineering to define data requirements and ensure product data flows into the data lake.

• Establish and maintain consistent metric definitions, data-quality standards, and analytical assumptions across products.

Communication & Influence:

• Develop dashboards, visualizations, and data narratives that make insights accessible and actionable.

• Translate complex quantitative findings into clear recommendations that influence product strategy, prioritization, and decisions.

• Champion the thoughtful, ethical, and high-quality use of data across the product organization.

What You'll Need

Key Qualifications

• Bachelor's or Master's degree in analytics, statistics, biostatistics, data science, economics, computer science, or a related quantitative field, or equivalent practical experience.

• 7+ years of experience in advanced analytics or applied data science supporting digital products in B2B or B2C marketplaces.

• Strong foundation in experimental design, causal inference, and statistical methods

• Advanced proficiency in SQL and Python or R, with experience working with large, complex datasets using Microsoft Azure technologies such as Synapse, Fabric, and PySpark notebooks.

• Proven ability to collaborate with cross-functional teams and influence product strategy and decisions.

• Strong communication skills, with the ability to translate complex analyses into clear insights and recommendations

• Ability to operate independently in ambiguous environments and foster a data-driven culture of learning and growth.

Preferred Qualifications

• Experience supporting B2B or multi-sided marketplace products.

• Experience applying advanced analytics and causal-inference methods to B2B product data.

• Experience with product instrumentation and experimentation tools such as Amplitude, Mixpanel, FullStory, or GA4.

Skills

• Analytical rigor: Applies advanced statistical and causal methods to break down ambiguous problems and uncover meaningful drivers, patterns, and opportunities.

• Measurement & Experimentation: Defines robust KPIs, develops reliable measurement frameworks, and leads A/B tests and quasi-experimental analyses that reduce uncertainty and accelerate learning.

• Product thinking: Connects product outcomes and experimentation to user behavior, value creation, and product strategy; influences direction through clarity and evidence.

• Data storytelling: Translates complex analyses into clear narratives and visualizations that influence priorities and align cross-functional teams.

• Collaboration and influence: Partners effectively within product teams, elevates analytical standards, and advances evidence-based decision-making.

• Bias for Action: Balances rigor with speed; focuses on insights that meaningfully shape decisions and outcomes.