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Alejandro Iborra Lucas
Data Scientist | Data Engineer @Ayesa
Alejandro Iborra Lucas is a Data Scientist and Data Engineer currently working at Ayesa.1 He is passionate about technology, business, and finance, with a particular focus on Data Science, entrepreneurship, and trading in financial markets.2
Professional Background
Alejandro's career journey has been driven by his interest in the financial markets. He became tired of losing money in these markets, which fueled his belief that "Without data, you're just another person with an opinion".1 This perspective likely motivated his transition into the field of data science.
Skills and Expertise
Alejandro has demonstrated proficiency in several key areas:
- Programming: He is skilled in Python, which is a crucial language for data science and engineering tasks.2
- Data Science: His current role at Ayesa involves working as a Data Scientist.1
- Data Engineering: In addition to data science, Alejandro also works as a Data Engineer.1
- Financial Markets: He has experience in trading financial markets.2
- Entrepreneurship: Alejandro is involved in entrepreneurial activities.2
Education
Alejandro's educational background includes training from Udacity1, which is known for its technology-focused online courses and nanodegree programs. This suggests that he has pursued specialized education in data science or related fields to complement his professional experience.
Location
Alejandro is based in Madrid1, which is likely where he carries out his professional activities for Ayesa.
Alejandro Iborra Lucas appears to be a multifaceted professional who combines his interests in technology and finance with his expertise in data science and engineering, contributing to his role at Ayesa and his personal endeavors in the financial markets.
Highlights
I’m happy to share that I’m starting a new position as Data Scientist | Data Engineer at SciTheWorld, Himitsu Tech!
After the recent spikes we’ve seen on bitcoin, decided to code a new tool to measure historic #volatility in any asset and then, perform a better #backtest on my #trading strategies.
In case you don’t have the data, find in the comments below the link to my other repo where you can find an easy to use tool that automatically collects tick data and converts it into your desired timeframe.
https://lnkd.in/gHjvGvE
This is a sample for the last month volatility in XBT but feel free to pass any other asset to obtain its volatility:
