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Aljosa Bilic

Aljosa Bilic

Zürich, Switzerland
Member since May 30, 2016
Aljosa is a data scientist and developer who has more than six years of experience analyzing noisy data sets, building statistical/predictive machine learning models, and designing and developing decision support tools and web apps that provide support for the front-end. He joined Toptal because freelancing intrigues him and the best projects and people are to be found here.
Aljosa is now available for hire
  • Statistics, 8 years
  • Data Science, 7 years
  • MATLAB, 4 years
  • Python, 4 years
  • Finance, 4 years
  • AngularJS, 3 years
  • Flask, 2 years
Zürich, Switzerland
Preferred Environment
OS X, PyCharm, Git
The most amazing... I've built is a commodity trading tool where I did the R&D of the price forward curve as well as built the back and front-end of the web interface.
  • Co-founder | CTO
    2016 - PRESENT
    • Co-founded a startup developing a web app (HTML, CSS, and AngularJS) and a cross-platform mobile app (Ionic Framework).
    Technologies: Python, HTML, CSS, JavaScript, AngularJS, Ionic Framework
  • Quantitative Analyst
    MET International AG
    2013 - 2016
    • Created a web-based commodity trading interface on top of a forward price curve generation algorithm for the straight-through order placement and processing of natural gas deals using Python for the numerical computation, STP, and web back-end and HTML, Bootstrap, and AngularJS for the front-end.
    • Developed a Monte Carlo-based method for the optimal pricing and hedging of natural gas storage and implemented it in Python (NumPy, Pandas).
    • Researched and developed a spread-based trading strategy on the German power markets and traded it live on the EEX.
    • Developed a detailed physical model for a natural-gas fired power plant and used it to derive optimal hedging and trading strategies.
    Technologies: Python, HTML, CSS, JavaScript, NumPy, Pandas
  • Quantitative Analyst
    swissQuant Group AG
    2010 - 2013
    • Developed a novel (non-heuristic) method for achieving higher asset diversification within the context of optimal portfolio construction and implemented it using MATLAB (computation) and Java (front-end).
    • Wrote a method for optimal hedging of currency exposure using arbitrary linear and non-linear instruments (e.g. options), based on normal or non-normal underlying distribution assumptions, and implemented a prototype using MATLAB and Java.
    • Created a method for tracking a non-investable insurance-linked securities index using a set of arbitrary investable products by modelling the index as a jump-diffusion process and minimising the CVaR of the performance difference.
    • Developed a method for hedging the future power generation of a wind farm connected to a liquid power market using liquid instruments.
    Technologies: MATLAB, Java
  • Languages
    Python, JavaScript, Java, HTML, R, SQL, SCSS, CSS, Less, C#
  • Frameworks
    Flask, AngularJS, Bootstrap, Ionic
  • Tools
    MATLAB, Sketch, RabbitMQ
  • Paradigms
    Data Science
  • Other
    Data Analysis, Bayesian statistics, Neural Networks, Machine Learning (ML), Statistics, Finance, Trading, Probability theory, Operations Research, Optimization, Applied Mathematics, Mathematics, Options Theory, Pattern recognition, Algorithmic Trading, Risk Management, Numerical Methods
  • Libraries/APIs
  • Platforms
  • Storage
    NoSQL, Microsoft SQL Server, MySQL, MongoDB
  • Erasmus certificate in Statistics and Financial Mathematics
    ETH Zürich - Zurich, Switzerland
    2009 - 2010
  • Master's degree in Engineering Physics
    Lund University, Faculty of Engineering LTH - Lund, Sweden
    2005 - 2010
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