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Georgiana Stan
Sector 6, Romania
CodersRank Score
What is this?
This represents your current experience. It calculates by analyzing your connected repositories. By measuring your skills by your code, we are creating the ranking, so you can know how good are you comparing to another developers and what you have to improve to be better
Information on how to increase score and ranking details you can find in this blog post.
135.4
CodersRank Rank
Top 5%
Top 10
Jupyter Notebook
Developer
Romania
Top 50
Python
Developer
Romania
Top 5
R
Developer
Romania
Highest experience points: 0 points,
0 activities in the last year
Python
68.3
exp.
Jupyter Notebook
46.2
exp.
JSON
2.8
exp.
List your work history, including any contracts or internships
Booking Holdings (NASDAQ: BKNG)
Dec 2024 - Mar 2025 (3 months)
Data Fraud Intern
Veridion
Jul 2024 - Sep 2024 (2 months)
Data Engineer Intern
An intense start-up experience, where I:
- transformed tens of columns into data points for easier querying and query latency reduction;
- implemented an efficient Spark-based data pipeline to process and webscrape thousands of pages;
- conducted advanced SQL queries for large databases and managed file storage using HDFS;
- was exposed to and customised ChatGPT-powered query pipelines to enable web search, increasing both time efficiency and accuracy;
- deeply analysed large-scale data and delivered actionable insights that informed decision-making;
- converted millions of rows of raw data into Parquet format and improved both query speed and storage efficiency;
- web crawled the internet.
- transformed tens of columns into data points for easier querying and query latency reduction;
- implemented an efficient Spark-based data pipeline to process and webscrape thousands of pages;
- conducted advanced SQL queries for large databases and managed file storage using HDFS;
- was exposed to and customised ChatGPT-powered query pipelines to enable web search, increasing both time efficiency and accuracy;
- deeply analysed large-scale data and delivered actionable insights that informed decision-making;
- converted millions of rows of raw data into Parquet format and improved both query speed and storage efficiency;
- web crawled the internet.
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