JOBSEARCHER

Data Analyst Intern

Location: In-PersonHours: 20–30 hours/weekDuration: 3–6 months (with potential to extend or convert)About MODMOD designs and delivers power, lighting, and infrastructure solutions for commercial office, healthcare, education, and hospitality environments. We’re a small, fast-moving team focused on building scalable systems, improving operational visibility, and making data-driven decisions as we grow.This role sits closely with senior leadership and offers hands-on exposure to strategy, operations, and analytics in a real operating business.What You’ll DoYou’ll help turn raw business data into clear insights and decision-ready dashboards. Responsibilities include:Build and maintain dashboards and reports across:Sales performanceInventory and SKU movementOperations and fulfillmentFinancial trends (revenue, margin, cash flow)Pull and clean data from systems such as:QuickBooksMonday.comHubSpotExcel / Google SheetsAutomate recurring reports (monthly, quarterly)Help define and track KPIs for different departmentsAnalyze trends and surface insights for leadershipSupport ad-hoc analysis for strategic and operational decisionsWhat We’re Looking ForCurrently pursuing a degree in Business Analytics, Economics, Engineering, MIS, Data Science, or a related fieldStrong Excel or Google Sheets skills (pivot tables, formulas)Comfortable working with messy or incomplete dataAnalytical, detail-oriented, and curiousAble to explain insights clearly (not just crunch numbers)Interest in operations, strategy, or business analyticsNice to HaveExperience with dashboards or BI tools (Power BI, Looker Studio, Tableau)Familiarity with QuickBooks, CRM systems, or ERP toolsBasic SQL or scripting experienceWhat You’ll GainDirect exposure to executive-level decision makingOwnership over real business analytics (not busywork)Experience building dashboards used by leadershipMentorship in strategy, operations, and data-driven managementOpportunity for extended engagement or full-time considerationCompensationHourly (based on experience)