Data Research Analyst (Must Know Python) - Internship

We are building the world's most accurate historical database for
international real estate. We do not rely on competitors; we go to the source.
We are looking for a data hunter, someone who refuses to accept 'data not
found' as an answer. You will be responsible for tracking down primary
economic and housing data from central banks, land registries, and national
statistics offices across 50+ countries.

Selected intern's day-to-day responsibilites include:

1. Source 'Unfindable' Data: Use advanced search techniques (Boolean
operators, deep web archives) to locate official historical datasets for
housing prices, rental yields, and inflation from government sources.
2. Data Cleaning & Standardization: Take messy "real-world" data (PDF tables,
non-standard Excel files, scanned images) and convert it into clean,
structured CSV/SQL formats using Python or advanced Excel.
3. Primary Source Verification: Rigorously document the provenance of every
data point. Log the specific government URL, date of access, and methodology
to ensure our data is legally independent and accurate.
4. Macro-Economic Analysis: Assist in mapping proxy metrics (e.g.,
construction cost index or GDP growth) to fill gaps in historical housing
data.