Aljosa Bilic, Developer in Zürich, Switzerland
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Aljosa Bilic

Verified Expert  in Engineering

Statistics Developer

Location
Zürich, Switzerland
Toptal Member Since
August 8, 2016

Aljosa is a data scientist and developer who has more than eight years of experience building statistical/predictive machine learning models, analyzing noisy data sets, and designing and developing decision support tools and services. He joined Toptal because freelancing intrigues him, and the best projects and people are to be found here.

Portfolio

InvestCloud
Recommendation Systems, Natural Language Processing (NLP)...
Klapp
Ionic, AngularJS, JavaScript, CSS, HTML, Python
Ava
Amazon Web Services (AWS), TensorFlow, Scikit-learn, Python

Experience

Availability

Part-time

Preferred Environment

Git, PyCharm, Jupyter, Python, OS X

The most amazing...

...project I've worked on is a statistical/ML-based flight delay insurance pricing engine.

Work Experience

Senior Data Scientist

2020 - 2023
InvestCloud
  • Spearheaded the development of a transformer-based text summarization and classification component for an investment research analyzer and security-level investment recommendation engine, significantly improving performance and value for clients.
  • Led the establishment of the data science SW architecture and CI/CD pipelines, improving deployment efficiency and operational scalability across the enterprise.
  • Contributed to the further development of the InvestCloud Portfolio Optimizer, applying advanced operations research and convex optimization methodologies to improve investment portfolio performance.
Technologies: Recommendation Systems, Natural Language Processing (NLP), Distributed Computing, Dask, PySpark

Co-founder | CTO

2016 - 2022
Klapp
  • Co-founded Klapp, single-handedly developing the initial MVP and driving the platform's adoption in 750+ schools and by 150,000+ parents in Switzerland.
  • Managed the technical architecture, back-end development, and coordination of near-shore front-end developers, establishing a robust and scalable solution.
  • Played a pivotal role in the startup's successful acquisition in 2022.
Technologies: Ionic, AngularJS, JavaScript, CSS, HTML, Python

Senior Data Scientist

2018 - 2019
Ava
  • Led the data science contribution to a novel product for detecting pregnancy anomalies, resulting in a new patent application.
  • Developed a sleep stage classification algorithm based on physiological data.
  • Performed user data mining for new insights and scientific publications.
Technologies: Amazon Web Services (AWS), TensorFlow, Scikit-learn, Python

Data Scientist

2016 - 2018
Swiss Re
  • Developed the weather model for a statistical/ML based flight delay insurance pricing engine.
  • Built a probabilistic global tsunami risk model.
  • Created an ML-based predictive model for insurance premiums and claims.
Technologies: Spark, R, Python

Quantitative Analyst

2013 - 2016
MET International AG
  • 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: Pandas, NumPy, JavaScript, CSS, HTML, Python

Quantitative Analyst

2010 - 2013
swissQuant Group AG
  • 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 modeling the index as a jump-diffusion process and minimizing 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: Java, MATLAB

Insurance-linked Securities Index Tracker

An article published in Bermuda:Re magazine; it describes the CVaR-based tracker that I developed for ILS Advisers.
2009 - 2010

Erasmus Certificate in Statistics and Financial Mathematics

ETH Zürich - Zurich, Switzerland

2005 - 2010

Master's Degree in Engineering Physics

Lund University, Faculty of Engineering LTH - Lund, Sweden

Libraries/APIs

Scikit-learn, Pandas, Underscore.js, Keras, Spark ML, Dask, NumPy, TensorFlow, Vue, PySpark

Tools

MATLAB, Jupyter, Tableau, PyCharm, Git, Sketch, RabbitMQ

Frameworks

Flask, Ionic, Bootstrap, AngularJS, Spark

Languages

Python, R, HTML, JavaScript, SQL, Java, Less, C#, CSS, SCSS

Paradigms

DevOps, Data Science, Distributed Computing

Industry Expertise

Banking & Finance

Platforms

Oracle, OS X, Amazon Web Services (AWS), Azure

Storage

NoSQL, MySQL, Microsoft SQL Server, MongoDB, Amazon S3 (AWS S3)

Other

Software Development, Machine Learning, Risk Management, Algorithmic Trading, Trading, Data Analysis, Neural Networks, Optimization, Statistics, Bayesian Statistics, Data Engineering, Data Modeling, Front-end Development, Airbnb, Mathematics, Applied Mathematics, Operations Research, Probability Theory, Numerical Methods, Options Theory, Pattern Recognition, Recommendation Systems, Natural Language Processing (NLP)

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