Strategy Analyst - E-Commerce Product Analytics

About the Role

Our client, a dental supply marketplace, is looking for a Strategy Analyst to join the Data and Analytics team and support the Product Management team responsible for building and improving the company's e-commerce website. This role will help Product Managers and UX Designers make better product feature decisions by analyzing customer behavior across the website, evaluating product changes, supporting experimentation, diagnosing funnel issues, and investigating anomalies in site performance.

This is a product-facing analytics role for someone who can use web analytics, clickstream-derived datasets, customer and order data, experiment results, and behavioral/session evidence to understand how users interact with the site and translate detailed behavioral analysis into clear recommendations. It is intended for someone who enjoys investigative analysis and deep dives into why performance changed.

Key Responsibilities

• Support Product Management with Data-Driven Decision-Making (20%): Partner with Product Managers and UX Designers to analyze website performance, customer behavior, and the impact of product changes. Help Product Managers understand what is working, what is not, and where the biggest opportunities are.
• Clickstream-Informed Behavioral Analysis (30%): Use governed web analytics and clickstream-derived datasets to support product analysis and customer journey diagnostics. Query event-level web behavior data using SQL. Move comfortably between detailed event-level investigation and executive-ready summaries of what changed, why it likely changed, and what action should be taken.
• Web, Funnel, and E-Commerce Journey Analytics (15%): Analyze user behavior across the e-commerce website to identify friction points, drop-offs, and opportunities to improve the customer experience.
• Anomaly Detection and Investigative Analysis (15%): Investigate unexpected changes in website behavior, funnel performance, conversion, revenue, traffic, or customer activity. Help Product and business teams quickly understand whether something is a real issue, what is likely driving it, and what action should be taken.
• Feature Prioritization and Trade-off Analysis (20%): Support Product Managers in using data to evaluate feature opportunities, prioritize work, and understand trade-offs across customer experience, conversion, revenue, operational complexity, and technical effort.

What Success Looks Like

• Acts as a thought partner to help Product Managers make better website feature and prioritization decisions with data
• Identifies friction points in the e-commerce customer journey
• Uses web analytics, clickstream-derived datasets, behavioral analytics, and customer/order data to understand product performance and customer journeys
• Improves the quality and reliability of experiment readouts
• Diagnoses anomalies in conversion, traffic, revenue, or behavior
• Connects web behavior to customer and order outcomes
• Uses behavioral analytics and session replay evidence to support deeper insights
• Flags tracking, instrumentation, sessionization, or data quality issues when they affect product analysis
• Communicates findings clearly and practically
• Pushes back when tracking, sample size, or data quality does not support a strong conclusion
• Turns ambiguous product questions into structured, decision-oriented analysis

Required Qualifications

• 3–6 years of experience in analytics, e-commerce analytics, product analytics, web analytics, digital analytics, growth analytics, strategy analytics, or a similar role
• Strong SQL skills, including experience working with large event-level, session-level, customer-level, or transaction-level datasets
• Experience analyzing website funnels, customer journeys, digital behavior, or e-commerce product experiences
• Curiosity and practical experience using generative AI and agentic AI tools to accelerate coding, SQL development, analysis, documentation, and day-to-day productivity
• Strong problem-solving skills and comfort working through ambiguous analytical questions
• Ability to translate detailed analysis into clear business recommendations
• Strong attention to data quality, metric definitions, and analytical assumptions
• Ability to work cross-functionally with Product, Engineering, Marketing, Enterprise Sales, Operations, and analytics stakeholders

Preferred Qualifications

• Experience with clickstream or event data from tools such as GA4 BigQuery Export, Adobe Analytics Data Feeds, Snowplow, or FullStory data exports
• Experience with web, e-commerce, product, or behavioral analytics tools
• Experience supporting experimentation or feature rollout analysis using tools such as Optimizely, VWO, AB Tasty, and Adobe Target
• Familiarity with event instrumentation, tag management, or customer data platforms such as Google Tag Manager, Segment, and Adobe Audience Manager
• Experience working with modern analytics and data tools such as SQL, Snowflake, dbt, Sigma, Looker, Tableau, Mode, Python, or R
• Experience in e-commerce, marketplace, retail, or digital product environments
• Familiarity with statistical concepts used in experimentation, such as confidence intervals, sample size, statistical power, p-values, and practical significance
• Experience investigating anomalies, behavioral changes, or unexpected metric movement across web, customer, and order data

Ideal Candidate Profile

The ideal candidate is highly collaborative, curious, analytical, and business-minded. They are comfortable working with messy website behavior data and can move from a vague product question to a structured analysis. They do not stop at "conversion dropped." They dig into where it dropped, who was affected, what changed, whether the tracking is reliable, what the event-level behavior shows, and whether the evidence is strong enough to recommend action.