Senior E-commerce Analyst
Senior E-commerce Analyst is a senior online store analyst who owns funnel data, unit economics, and decisions on assortment, advertising, and pricing, working with growth and finance teams.
What a Senior E-commerce Analyst does
The Senior E-commerce Analyst ensures that decisions about the online store are based on data. They build reporting on the purchase funnel, margin, returns, and repeat orders, test the growth team's hypotheses, and explain why metrics have changed. In highly competitive verticals with thin margins, this role directly influences which categories to scale and which to stop.
In the company, this role usually reports to the Head of Analytics or the e-commerce lead and works closely with the category manager, performance marketer, product analyst, and financial controller. At the senior level, the analyst formulates business questions independently, chooses the methodology, defends conclusions to leadership, and often manages 1-2 junior analysts or interns.
Working in e-commerce within high-risk verticals (for example, nutra products, digital goods, or subscriptions) adds specific challenges: cancellations and chargebacks distort revenue, payment declines affect conversion, and platform and ad network restrictions require careful attribution. A good analyst understands these limitations and does not present noisy figures as facts.
Responsibilities
- Build and maintain dashboards for the funnel: traffic, add-to-cart, checkout, payment, order fulfillment, and repeat purchases
- Calculate unit economics by SKU, category, and channel: gross margin, acquisition cost, logistics, returns, and payment processing fees
- Analyze the causes of revenue and margin deviations and formulate specific recommendations for teams
- Design and analyze A/B tests for pricing, product pages, checkout, and discount mechanics
- Maintain demand forecasting and inventory models together with purchasing and operations teams
- Set up end-to-end analytics and order attribution across advertising channels, the website, and CRM
- Monitor data quality: reconciliation with accounting, duplicate orders, payment and refund statuses
- Prepare regular reports for management with conclusions, not just charts
- Advise category managers and marketers on data and methodology, and train junior analysts
- Contribute to requirements for internal data collection and storage systems
Skills
- Advanced SQL, including window functions and joining multiple data sources
- Understanding of online store unit economics and the difference between revenue, margin, and profit
- Statistics for experiments: test power, confidence intervals, and common interpretation errors
- Dashboard building and the ability to simplify complex pictures for non-technical audiences
- Working with attribution and understanding its limitations when data collection rules change
- Hypothesis testing and prioritization by expected impact and cost of testing
- Communication: defending conclusions in front of leaders who dislike uncomfortable numbers
- Understanding of delivery, returns, and payment decline processes that affect metrics
- Mentoring and code review of analytical queries and models
Tools
- Google BigQuery or ClickHouse
- SQL clients and dbt for data modeling
- Looker Studio, Tableau, or Power BI
- Google Analytics 4 and server-side event tracking
- Python (pandas) or R for analysis and models
- Spreadsheets and Google Sheets for quick calculations and reconciliations
- Jira or Trello for task management and experiment tracking
- Online store order management and CRM systems
How performance is measured
- Accuracy of revenue and margin reconciliation with financial data
- Response speed to business requests and turnaround time for on-demand analytics
- Share of decisions made based on completed analyses and tests
- Experiment quality: share of properly planned tests with sufficient sample size
- Relevance and accessibility of dashboards for teams
- Contribution to margin growth or return reduction in categories the analyst oversees
By vertical
E-Commerce
In a classic online store, the main focus is on the purchase funnel, stock availability, logistics, and returns. The analyst often works with catalogs of hundreds or thousands of SKUs and is responsible for identifying which categories generate margin after delivery and returns.
Levels
Senior
A senior analyst independently leads an analytics area (for example, all categories or an entire acquisition channel), formulates business questions, selects methods, and is accountable for the quality of conclusions. They mentor junior colleagues and take part in decisions on team priorities, rather than only executing queries.
How to get there
People usually enter the profession from product or marketing analytics, financial analysis, BI development, or operational e-commerce roles where they already worked with exports and reports. What matters most is proven experience with real online store data and the ability to explain which decision your conclusions changed.
What to learn first: SQL at the level of confident selections and aggregations, the basics of online store unit economics, basic statistics for A/B tests, and dashboard design principles. It is also useful to understand how orders, payment statuses, returns, and fees work, since metrics most often break down at these points.
Growth comes from expanding your scope: from reports on a single category to end-to-end analytics for the whole channel, from ready-made exports to your own models and experiment methodology, and from executing queries to shaping recommendations for leadership. A sign of senior level is that your conclusions change decisions, rather than just describing the past.
Next steps: Lead Analyst or Analytics Team Lead, Head of Analytics (e-commerce), Product Analytics Lead, Growth Analytics Manager, Category Manager with analytical expertise
FAQ
How is a Senior E-commerce Analyst different from a regular data analyst?
A regular analyst often completes tasks on request, while a senior owns the entire area: they choose what to measure, defend conclusions to management, and influence priorities. A senior also mentors junior analysts and is responsible for data quality in their area.
Is experience in high-risk e-commerce verticals required?
Direct experience is valued but not mandatory if you understand the general specifics: cancellations, returns, payment declines, and advertising platform restrictions. It is important to explain how these factors distort metrics and to show that you do not trust numbers without verification.
Which tools should I know first?
The foundation is SQL, a BI tool (Looker Studio, Tableau, or Power BI), Google Analytics 4, and spreadsheets. For more complex tasks, Python or dbt are useful, as is an understanding of how the company's data warehouse works. The exact stack depends on the employer.
What determines a Senior E-commerce Analyst's income?
Income depends on the size of the company and the online store's turnover, the scope of responsibility (one category or the entire channel), data complexity, and whether management duties are included. It also matters significantly how closely the analytics work is tied to decisions that affect profit.
What is the career path for this role?
The most common directions are Lead Analyst or heading an analytics team, or moving into product or growth analytics. Some analysts move into category management if they enjoy making decisions about assortment and pricing.
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