JULIAN PANERO

As a graduate in Physics and a naturally curious individual, I strongly believe I could bring valuable expertise to the team due to my strong foundation in mathematics, statistics, and data science.

During my physics studies, I was able to acquire a huge and varied mathematical knowledge as well as Data Science experience, which I further enhanced through online courses to broaden my programming skills. 

Additionally, I majored in Meteorology, Climatology, and Geophysics. This foundation, combined with further studies and in-depth exploration, has granted me profound knowledge in the field.

In my roles as a data scientist and market risk consultant, I had the opportunity to apply my statistical and data science skills, gaining new insights in finance, especially in the context of market risk.
Additionally during my tenure at Management Solutions I attended a Master’s in Business Consulting. This program exposed me to various aspects of business, including macroeconomics, accounting, and industries like energy, telecommunications, and banking. I also delved into subjects related to credit risk and market risk.

Currently I am pursuing an online master’s degree in Data Science in order to continue learning about the topic during my free time.

My diverse skill set, combined with my eagerness to expand my knowledge, makes me a versatile candidate capable of contributing effectively in various areas.

• Linear and Non-Linear Products Pricing: This was done to validate the calculations performed by Murex using the data displayed within Murex.

• Implementation of Full Revaluation Method for VaR in Murex 3: The creation of the shocks used by Murex to calculate various metrics. These shocks were generated using Python and historical data of interest rate curves, FX spot rates, and volatility smiles.

• Full Automation of Validation Processes for Different FRTB-IMA Metrics:

     - VaR/SVaR Validation: The creation of a Python program to compare values obtained in Murex and the program previously used (AIRE). This program showed the correlation of scenarios, a                   comparison of the distribution, and a graphical comparison of the values. The results were presented both in total and per book.

     - RTPL vs. HPL: The creation of a program to compare values to ensure they do not exceed the limits. Also showed a comparison of the interest rate curves that were interpolated in diferente ways in each metric.

• Risk Not in the Model Calculation and Visualization with Atoti: A tool was developed to measure Z-Spread risk. The tool was created in Python using Atoti for visualization.

Bachelor of Science in Physics:  Meteorology, Climatology, Geophysics, Mathematical Methods, Programming and Data Analysis.

Master’s Degree in Data Science: Machine Learning, Databases and Data Visualisation.