Stephen Bieniek, Data Analysis Developer in London, United Kingdom
Stephen Bieniek

Data Analysis Developer in London, United Kingdom

Member since February 11, 2020
Stephen Bieniek started his career as a physicist working on the Large Hadron Collider at CERN. His job was to analyze vast quantities of data to understand the behavior of the building blocks of the universe. After getting his fill of academia, he moved into trading where instead of trying to understand the universe he needed to understand the financial markets. In both ventures, the key parts of the data analysis were statistical rigor and interpretable results.
Stephen is now available for hire

Portfolio

Experience

  • Data Science 13 years
  • Data Analysis 13 years
  • Quantitative Analysis 13 years
  • Quantitative Modeling 10 years
  • Algorithmic Trading 5 years
  • Futures 5 years
  • Trading 5 years
  • Algorithmic Trading Analysis 5 years

Location

London, United Kingdom

Availability

Part-time

Preferred Environment

SQL, C++, Python, Unix

The most amazing...

...thing I've developed is a method to simulate sub-atomic particles much more efficiently allowing a huge increase in model accuracy.

Employment

  • Quantitative Trader

    2014 - 2019
    XR Trading
    • Developed a trading strategy that made $10,000 a day.
    • Automated the majority of daily tasks to spend more time on research.
    • Developed a set of research tools which was shared by the entire team.
    Technologies: Unix, C++, Python
  • Physicist

    2009 - 2013
    CERN
    • Increased vastly the efficiency of simulating a sub-atomic particle.
    • Conducted research on a dataset measured in petabytes.
    • Presented research to the best minds in the world.
    Technologies: Root Cause Analysis, Unix, Python, C++

Experience

  • Housing in Liverpool
    https://applied-data.co.uk/2020/02/12/housing-as-a-portfolio/

    A study into the profitability of purchasing a portfolio of buy-to-let properties. The aim was to deduce a set of parameters and rules in which the business could be profitable. The study modeled the cash flow of running a property business and it tested different scenarios.

  • Measurement of the Inclusive and Dijet Cross-sections of B-jets in PP Collisions
    https://arxiv.org/pdf/1109.6833.pdf

    The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a center-of-mass energy of √s = 7TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34pb−1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors or a muon-based method where the presence of a muon is used to identify semi-leptonic decays of b-hadrons inside jets.

  • Measurement of the BB-dijet Cross-section in PP Collisions at √s = 7TeV with the ATLAS Detector
    https://arxiv.org/pdf/1607.08430.pdf

    The dijet-production cross section for jets containing a b-hadron (b-jets) has been measured in proton-proton collisions with a center-of-mass energy of √s = 7TeV, using the ATLAS detector at the LHC. The data used correspond to an integrated luminosity of 4.2fb-1.

  • Modeling a Sales Team
    https://applied-data.co.uk/2020/03/25/modelling-the-sales-process/

    This article explores using statistical methods to simulate a sales team. From the sales team simulation a set of "historical" training data is created to fit model which can predict the value of any sales prospects which have not been closed. The predictions are provided as a band giving the upper and lower revenue estimate to a 95% confidence interval. This research acts as a proof of principle that such techniques are be able to be to provide useful information to sales managers.

  • Evaluating Cities as Buy-to-let Investment Opportunities.
    https://applied-data.co.uk/2020/03/27/evaluating-cities-as-buy-to-let-investment-opportunities/

    In my previous posts I looked at buying a house to rent in Liverpool. I chose Liverpool based upon some brief research on Zoopla. I picked a handful of UK cities, and searched for two bedroom flats near the city center for sale and rent. Based on these figures I calculated a rough rental yield and Liverpool was seen to be the best. However, this was a very rough piece of research which left a lot of room for improvement. Making use of freely available data on the internet I should be able to improve this search to look at all cities within the UK to make sure I do not miss any opportunities.

Skills

  • Paradigms

    Data Science
  • Other

    Quantitative Analysis, Data Analysis, Trading, Algorithmic Trading, Algorithmic Trading Analysis, Quantitative Modeling, Machine Learning, Futures, Root Cause Analysis
  • Languages

    Python, C++, SQL
  • Platforms

    Unix

Education

  • Doctor of Philosophy degree in Physics
    2009 - 2013
    UCL | University College London - London, UK
  • Master of Science degree in Physics
    2005 - 2009
    Royal Holloway, University of London - Surrey, UK

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