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Graduate research project at IE Business School analyzing Glencore, BHP, and Rio Tinto using a proprietary SASB-weighted ESG scoring model built via Bloomberg Terminal. Assessed material ESG risks across the global mining sector and translated raw data into structured investment-grade analysis.
Skills: ESG Research, Quantitative Analysis, Sector Research
Tools: Bloomberg Terminal, Excel, PowerPoint
The network for creativity
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Connect with clients, get discovered, and run your business 100% commission-free
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High-Ticket Lead Generation: Houston Roofing Decision Makers 🏗️💎
In the construction industry, generic leads are a waste of time. For this project, I moved beyond simple scraping to find verified decision-makers (Owners, CEOs, and Operations Managers) for roofing firms in the Houston, Texas area.
My specialized workflow for this project:
1️⃣ Deep-Niche Research: Targeted companies specifically in the $1M–$10M revenue range to ensure they have the budget for high-end services.
2️⃣ Human-in-the-loop Verification: Every email and direct dial was cross-referenced to ensure no gatekeepers and no bounces.
3️⃣ Intent Mapping: Identified firms currently scaling their teams, indicating a higher need for external partnerships.
The Result: A clean, high-intent list delivered in under 24 hours, ready for immediate outreach.
👇 Check the "Completed Work" link below to see the quality of the data!
NIce
Analytics snapshot showing improved reach and engagement through structured content — with over 80% reach coming from non-followers via reels, helping drive discovery and potential conversions.
This project showcases my ability to transform messy, unstructured data into clean, organized, and actionable insights using Excel.
I worked with raw datasets containing inconsistencies such as duplicate entries, inconsistent formatting, and missing structure. I cleaned and standardized the data, ensuring accuracy and consistency across all fields.
From there, I built organized tables and dashboards to highlight key metrics such as revenue, profit, and performance by category and region. I also used formulas (including SUMIFS and calculated fields) to automate insights and improve usability.
This type of work is ideal for clients who need:
Clean and structured data
Reliable reporting
Easy-to-read dashboards
Improved data accuracy
The end result is a clear, professional spreadsheet that turns raw data into meaningful insights.
The before and after view of the data cleaning really shows the value clearly — clients often don't realise how much time messy data costs them until they see it laid out like this. The monthly sales dashboard with KPIs on top is a clean layout too. Did you build this for a real client or as a portfolio piece?
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