Associate Data Insight Analyst

Job Summary:

This role supports foundational analytics for our grocery and eCommerce business. You will help design dashboards, run queries, and build basic analytical summaries that support decisions across marketing, loyalty, merchandising, and omnichannel operations. This role is ideal for someone who wants to strengthen their analytical fundamentals and grow into more advanced statistical and modeling work.

Role and Responsibilities:

Reporting & Dashboarding:

• Build and enhance dashboards (Power BI, Tableau) to monitor sales performance, loyalty activity, customer funnel conversion, and digital engagement.
• Maintain basic KPI scorecards and ensure accuracy through routine data validation and consistency checks.

Analysis Execution:

• Write SQL queries to extract and clean datasets for routine reporting and exploratory analysis.
• Perform descriptive analytics: trend analysis, variance analysis, cohort tables, and basic correlation analysis.
• Conduct simple customer analyses such as RFM scoring, retention tracking, and promotional impact summaries.

Experimentation Support:

• Assist in A/B testing setup by pulling test/control samples and producing simple significance testing outputs (t-test, proportion tests).

Collaboration & Documentation:

• Work with U.S. analytics partners to refine reporting needs, automate recurring tasks, and document analytical workflows.
• Maintain organized data dictionaries, metric definitions, and report documentation to ensure consistency across teams.
• Validate data accuracy through statistical quality checks, outlier detection, and variance analysis.
• Partner with senior analysts to learn foundational statistical methods like linear regression, clustering basics, and forecasting.

Required Experience:

• Bachelors degree in Analytics, Statistics, Engineering, Business, Economics, or related fields.
• 12 years of experience in analytics or reporting (retail/eCommerce experience preferred).
• Strong SQL and Excel experience; familiarity with functions for summarization, pivoting, and basic statistical formulas.
• Experience with visualization tools (Power BI, Tableau).
• Strong interest in developing skills in regression, clustering, forecasting, and experimentation.
• Understanding of KPIs commonly used in retail/eCommerce (conversion, retention, AOV, unit movement, loyalty tiers).
• Ability to communicate data insights clearly to non-technical stakeholders.