Ilyès kerkeni

👋 About

Linkedin, E-mail, Phone

Hello, I'm Ilyès, a final year engineering student in applied mathematics at ENSTA Paris and a Master 2 student in “Probabilités et Finance” (formerly DEA El Karoui). I have a passion for quantitative finance and machine learning as applied to financial markets, and I've developed strong analytical skills and a deep understanding of mathematical modeling. I've gained valuable experience as a quantitative researcher trainee, where I developed sophisticated models for autocallable products and conducted calibrations for var swaps, covar swaps, vol swaps, and options. Following this, I worked as a quant-data scientist trainee, where I applied advanced statistical techniques to extract insights from complex financial data. Currently, I'm interning at Goldman Sachs as a quant strategist on the FX team. I'm committed to continuous learning and driven by a passion for innovation. I'm excited to make meaningful contributions to the field of quantitative finance, helping to drive success for my organization.

💼 Professional Experience

Quantitative Strategist
Goldman Sachs

London, UK
May 2024 - Now

  • Off Cycle Internship
  • Designing and implementing a ”Time - dependent Heston” model and Conducting rigorous calibration.
  • Ongoing.

Quantitative trader (full remote)
Eruditis

Milwaukee, USA
Juin 2022 - April 2024

  • Part Time job (Freelance)
  • Exploring and implementing trading strategies using Machine Learning and reinforcement Learning.
  • Implementing research papers.

Quant-Data scientist
Crédit Agricole CIB

Paris, France
01 March 2023 - 31 August 2023

  • Project for USD VOL DESK
  • Working side to side with the IRD exotic trader and the head of AI GMD department to make financial market predictions and modeling
  • Collecting and analyzing data from US insurers, forward rates, implied volatilities, and index values to anticipate and explain insurers’ trading activities.
  • Building and maintaining new models, gaining 20points in performance.

Quantitative Researcher
HSBC Paris

Paris, France
29 August 2022 - 28 February 2023

  • Research Project under the aiges of “Europlace Institut of Finance”
  • Working with both machine learning models and multivariate rough volatility models, gaining expertise in the randomized signatures (rSig) pricing model and the quadratic Gaussian (qGauss) models.
  • Developing rich models that remain numerically tractable for the fast generation of autocallable prices and sensitivities.

Quantitative Reasearcher
Crest, Ensae Paris

Paris, France
1 Juin 2022 - 19 August 2022

  • Exploring several approaches to estimate VaR and CoVaR using Parametric Models, Non-parametric models, Semi-parametric models
  • Garch models, Monte carlo simulation, resampling, bootstrapping, python/R programming

🎓 Education

M.S. “Probabilitées et finance ex DEA EL KAROUI”
Ecole Polytechnique - Sorbonne University

Paris, France
September 2023 - 2024

  • Courses: Machine Learning-Neural Networks-Deep Learning, Stochastic control and optimisation, High-frequency finance: probabilistic tools, statistical modeling, Machine learning and optimal trading etc..
  • GPA=4

Enginnering degree
Ensta Paris

Paris, France
September 2020 - 2024

  • GPA=4
  • Applied Mathematics (Statistics, Probability, Markov chains, Stochastic calculus, Optimization, Martingales, Time series, Monte-Carlo Methods, Machine learning, mathematical models in finance).

🏆 Projects

  • Team enginner project H1N1 & flu predictions The aim is to predict whether a person is vaccinated against H1N1 and seasonal flu. we used here vast majority of classification mdeols (tree based models: XGboost, Catboost, RandomForest) neural networks ect..
  • Predicting rent Prices
  • Image Classififcation deploying a convolutional neural networks (with C) capable of classifying images according to their categories.
  • Algorithmic Trading on Stocks (via IBKR API) and on Cryptos (via Binance API) The aim here is to build statistical arbitrage strategies on different markets, implement them in Python, and apply them to Interactives Brokers.

💾 Resume

🎖️ Certifications

💻 Technical skills

  • Python : Pandas, numpy, Sikit-Learn, Pytorch, Tensorflow, Keras
  • C++, C
  • Matlab
  • R
  • Excel, PowerPoint, LaTex
  • Dataiku, IBM waston studio

🎳 Hobbies

  • Reading 📚

  • GYM 🏋🏻‍♀️ and Swimming 🏊🏻‍♂️ (Almost 5 days per week)

  • Tennis 🎾 (Rafa Nadal)

  • (Ex) professional basketball player 🏀 .

  • Traveler 🧳.