Philip Spanoudes

Machine Learning Engineer

San Francisco, California

Data Scientist with a specialization in the design and implementation of deep/machine learning algorithms. Industry experience in: predictive modeling, optimization problems and simulations.

Work Experience

  • Square Inc.

    Data Scientist|May, 2016Current

    Part of the initial Square Capital Data Science team that was tasked with the continual optimization of all lending product design, marketing strategies and servicing techniques.

    • Improved the internal rate of return (IRR) forecasting model for the Capital Flex product.
    • Designed and implemented a product simulation framework that is used to evaluate the effects of model swaps and loan facilitation methodology alterations.
    • Designed and implemented a heuristic optimization framework for product eligibility that searches for optimum threshold configurations based on expected loss and volume.
    • Designed and implemented an email servicing model for automated solution suggestions to email inquiries.
    • Improved the pre-existing loss forecasting model for the Capital Flex loan product.
    • Designed and implemented an account servicing model that is used to identify high risk customers.
    • Designed and implemented a Capital acceptance model for the marketing team that uses merchant event patterns to determine the probability of product acceptance.
    • Created and was responsible for the team's model hosting framework and development environment.
  • Framed Data

    Data Scientist|Nov, 2015Apr, 2016

    Hired as Framed Data's principal research scientist with the sole task of improving the company's churn prediction algorithms for each customer.

    • Researched and implemented a novel machine learning pipeline for arbitrary customer churn prediction.
    • Invented a generalized data representation architecture that can be applied on different raw event company data.
    • Implemented a state-of-the-art Deep Learning architecture that effectively decomposed complex user event patterns and ultimately increased prediction accuracies.
  • Flight Data Services

    Data Science Intern|May, 2014Aug, 2014

    Summer Data Science internship which helped in the uncovering of interesting patterns in flight sensory data to help with our flight operation quality assurance reporting to customers.

    • Applied statistical analysis, machine learning and data mining techniques on vast amounts of flight sensory data.
    • Identified patterns and interesting associations between combinations of flight data variables.
    • Designed and generated visualizations that helped with the interpretation and explanation of the identified patterns within the FOQA product.
  • NCR Corporation

    Software Developer|Jun, 2012Aug, 2013

    One year placement at NCR (EMEA HQ) as part of the BSc. (Hons) Sofware Engineering course at the University of Portsmouth.

    • Developed parts of the system that are currently being used by the Inland Revenue Department in Cyprus.
    • Experienced different development life-cycles including Agile methodologies.
    • Performed extensive Testing and produced Product Manuals for audiences of various technical knowledge.


  • Lancaster University (UK)

    Master of Science in Data Science - Distinction|Sep, 2014Nov, 2015

    Best Overall Student Performance Award: Prestigious award in recognition for best student performance across all degree modules.

  • University of Portsmouth (UK)

    Bachelor of Science in Software Engineering - First Class Honours|Sep, 2010May, 2014



    • Machine Learning
    • Deep Learning
    • Feature Engineering
    • Python
    • Java
    • C++
    • Apache Spark
    • C#