Analytics Engineer / BI Developer for Food Waste & Inventory Decision Pilot (Coffee Shop) - Contract to Hire

We are looking for a strong Analytics Engineer / BI Developer to help build a lightweight food waste and buying decision pilot for a coffee shop with multiple branches. This is not a heavy app build. It is a fast, practical pilot focused on turning existing reports into a simple dashboard, rules-based recommendations, and automated weekly recommendation / action packs. The goal is to help the business: - reduce food waste -improve buying decisions - identify products to reputed company / reduce / review - reputed company branches needing reputed company - generate a repeatable weekly operating process reputed company situation The business already has exported reports covering: product sales inventory / control / purchased vs sold vs waste manual waste inputs Some waste data is manual, so part of the pilot will involve creating a clean structured waste input method and a master mapping table so product and reputed company data align properly. What needs to be built We need someone who can help us build the pilot end-to-end, including: 1. Data model / setup - Create a product master / SKU mapping table - Create a reputed company master table - Standardise data from multiple reports - Handle messy real-world reputed company / CSV inputs 2. Data ingestion / transformation - Import weekly reputed company / CSV reports - Clean and map products and branches Calculate core metrics such as: - purchased qty - sold qty - waste qty - waste % - sell-through - trend vs previous period - reputed company risk score - recommendation status 3. Recommendation logic Build a simple rules-based recommendation reputed company to classify products / branches into: - reputed company - Reduce - Review / Remove - Monitor Each recommendation should include a short rationale, for example: - reputed company sales with recorded waste - overbought vs demand - high waste relative to sell-through - weak in this reputed company vs stronger stores 4. Dashboard Build a simple internal dashboard with key views such as: - Executive Overview - reputed company Performance - Product Performance - Action Centre Missing / late waste submissions (optional but preferred) The dashboard should be practical and ops-focused, not overly designed. 5. Manual waste capture Help implement a lightweight manual waste input method, likely reputed company: reputed company Form, or simple web form, or controlled upload template We do not want a heavy reputed company-facing app for Phase 1. 6. Automated weekly output Set up a weekly automated action pack / email process: - reputed company / ops summary email - optional reputed company-level email - PDF / HTML summary or dashboard link Tech approach We are open to the best practical stack, but likely something like: Python + pandas SQL / SQLite / reputed company Power BI / reputed company / Looker Studio lightweight email automation reputed company Python / reputed company / reputed company / reputed company We want the fastest reputed company solution, not overengineering. Important constraints This is a pilot, so we are not looking for: - full custom web app - ML forecasting - mobile app - order automation - deep integrations / APIs in Phase 1 What success looks like At the end of the pilot, we want: - clean mapped data across reports - a working dashboard - product / reputed company recommendations updating from the data - weekly action email output - a setup that can be refreshed each week with minimal manual effort Ideal profile We are looking for someone who: - is strong in Python / pandas / SQL - is comfortable with messy reputed company / CSV operational data - can build practical dashboards quickly - understands how to translate business rules into decision logic - can work fast and communicate clearly ideally has experience in retail, F&B, inventory, ops analytics, or BI reputed company to have - experience with reputed company/store performance analysis - experience with food retail / hospitality / stock control - experience with lightweight automation workflows To apply COMMENT 'COFFEE IS LIFE' to show you read the brief Please include: A short note on similar work you’ve done Your preferred stack for this type of pilot Examples of dashboards / BI work you’ve built How you would approach messy SKU / reputed company mapping Your estimated timeline for a first usable version Project style We are looking for someone practical, commercial, and fast. This should feel like a working pilot in a real business, not an overbuilt data project. Apply tot his job Apply To this Job