Contact person: Business Client

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Location: Pécs, Hungary

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"Esteemed Freelancers!

Thank you to everyone who submitted a proposal and showed interest in the project!
Since the offers vary widely in both scope and pricing, I’ve decided that, for better clarity and evaluation, I will split the data collection and organization work into five separate projects.

Each project will be uploaded individually here on Freelancer, with detailed specifications and clear requirements.
This will make it easier to identify which freelancer is best suited for each specific task.

The overall goal is to establish a long-term, multi-project collaboration with a research-oriented data professional who works with precision and thorough documentation.

In addition, I will soon announce two separate big data-oriented projects focusing on the application of Machine Learning and Explainable AI methods, including SHAP, XAI, XGBoost, and LIME, for advanced analytical modeling and interpretability tasks.



Data collection and organization for research datasets (EU27, S&P500, STOXX600, or similar sources)

Project description:

I’m looking for a detail-oriented freelancer to assist with data collection and structuring for research purposes. The project involves compiling, organizing, and documenting data from reliable public sources — such as Eurostat, IMF, World Bank, AMECO, Yahoo Finance, Refinitiv, or corporate reports — according to a predefined structure.

The dataset may cover:
Country-level data (e.g., EU27, OECD), or Firm-level data (e.g., S&P500, STOXX600).
Specific variables and templates will be provided after selection.
This is a data preparation and standardization task, not analysis.

Main tasks:
a) Collect data from listed official or public sources
b) Structure the data into a panel format (country/company × year × variables)
For each variable, provide:
Source URL
Download date
Unit or definition
Deliver final files in .xlsx and .csv formats
Include a short documentation file ([login to view URL] or separate sheet) describing variables and sources

Requirements:
Accuracy and clarity in data handling
Only verifiable, public data sources
Missing values clearly marked as NA
Must sign a Non-Disclosure Agreement (NDA)

Advantage: experience with Excel, Python/R, or statistical databases

Deliverables:
1 .xlsx file
1 .csv file
1 documentation file ([login to view URL] or sheet)" (client-provided description)