Carina van der Zee, Data Scientist and Developer in London, United Kingdom
Carina van der Zee

Data Scientist and Developer in London, United Kingdom

Member since July 29, 2022
Carina is an expert in data analysis and visualization, statistical modeling, and machine learning. With over five years of experience in some of the top Wall Street banks, she is comfortable working with small and big data problems. After obtaining her bachelor's and master's degrees in mathematics, engineering, and business, Carina realized notable professional achievements as a front-office quantitative researcher.
Carina is now available for hire

Portfolio

Experience

Location

London, United Kingdom

Availability

Part-time

Preferred Environment

Python 3, PyCharm, Visual Studio, Bitbucket, Slack, Skype, Tableau, Microsoft, Python, Machine Learning, Data Science, Data Analytics

The most amazing...

...model I developed increased my client's profitability by 50%.

Employment

  • Vice President, Quantitative Research

    2020 - 2022
    JPMorgan Chase
    • Developed statistical models for the fixed-income trading desks to predict market moves, trading and client volume, and more. These models incorporated both traditional statistical models and machine learning models.
    • Analyzed high-frequency market data using KDB, Q, and Python.
    • Created data visualizations using Tableau and Python plotting libraries such as Seaborn and Plotly.
    • Prepared technical documentation in LaTeX and Confluence.
    Technologies: Python, Statistical Modeling, Mathematics, Probability Theory, Data Visualization, Tableau, SQL, Data Science, Artificial Intelligence (AI), Data Engineering, Predictive Analytics, Data Analytics, Data Analysis, Predictive Modeling, Amazon Web Services (AWS), Real-time Data, Computer Vision, Cloud, Neural Networks, Machine Vision, Image Processing, MongoDB, Data Modeling, Data Reporting, Data Mining, Time Series Analysis, Time Series
  • Quantitative Analyst

    2018 - 2020
    Barclays Corporate and Investment Bank
    • Developed a statistical model to predict the bank's funding costs in several stress scenarios.
    • Created technical documents in LaTeX to provide a detailed description of the model implementation and model development research.
    • Oversaw the production release process, liaising with many coders and ensuring the production codebase's continuous quality and functionality.
    Technologies: Python, Git, Statistics, Machine Learning, Technical Writing, LaTeX, Jira, R, Data Science, Artificial Intelligence (AI), Predictive Analytics, Data Analytics, Data Visualization, Data Analysis, Predictive Modeling, Neural Networks, MongoDB, Data Modeling, Data Reporting, Time Series Analysis, Time Series

Experience

  • Predictive Model for Mortgage Prepayment Rates

    A Python-based statistical model that predicts mortgage prepayment rates given the portfolio characteristics. I conducted the complete data analysis, feature engineering, model development, and production code implementation.

  • Multivariate Timeseries Prediction for Cryptocurrencies

    Trained, tested, and compared several predictive models (VARMA(X), XGBoosted tree, RNN, copula) to predict the price moves of multiple cryptocurrencies. Compared several predictive power for different time windows and investigated potential explanatory variables (besides AR/MA components).

  • Develop Trade Strategies Around Market Events

    Developed and backtested trade strategies around market events based on several predictive models for market indicators. Used several techniques, including time series modeling, copula techniques, deep learning, and reinforcement learning.

Skills

  • Languages

    Python 3, Python, SQL, R
  • Paradigms

    Data Science
  • Other

    Statistics, Probability Theory, Statistical Modeling, Data Analysis, Mathematics, Time Series Analysis, Hypothesis Testing, Data Visualization, Machine Learning, Predictive Analytics, Data Analytics, Predictive Modeling, Real-time Data, Image Processing, Data Modeling, Data Reporting, Time Series, Deep Learning, Bayesian Statistics, Neural Networks, Artificial Intelligence (AI), Computer Vision, Machine Vision, Data Mining, Email, Google Colaboratory (Colab), Business, Finance, Financial Markets, Business Psychology, Marketing Mix, Mechanics, Presentations, Technical Writing, Recurrent Neural Networks, Convolutional Neural Networks, Image Recognition, Data Engineering, Cloud, Copulas, Deep Reinforcement Learning
  • Tools

    Visual Studio, Tableau, PyCharm, Bitbucket, Slack, Skype, Git, GitHub, LaTeX, Jira
  • Platforms

    Ethereum, Blockchain, Microsoft, Amazon Web Services (AWS), Azure
  • Storage

    MongoDB, Google Cloud
  • Libraries/APIs

    TensorFlow, Keras

Education

  • Master's Degree in Applied Mathematics
    2016 - 2018
    Delft University of Technology - Delft, The Netherlands
  • Bachelor's Degree in Business Administration
    2012 - 2016
    Erasmus University Rotterdam - Rotterdam, The Netherlands
  • Bachelor's Degree in Engineering
    2011 - 2016
    Delft University of Technology - Delft, The Netherlands

Certifications

  • Deep Learning
    JANUARY 2019 - PRESENT
    Coursera

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