Carina van der Zee, Developer in London, United Kingdom
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Carina van der Zee

Verified Expert  in Engineering

Data Scientist and Developer

London, United Kingdom
Toptal Member Since
July 29, 2022

A seasoned AI/ML and statistics expert, Carina leverages her comprehensive skill set to deliver impactful solutions as a consultant, freelance, and CTO. Her impressive trajectory spans from top Wall Street banks to technical leadership in the tech sector, backed by robust academic credentials in mathematics, engineering, and business. Passionate about solving analytics, automation, and optimization challenges, Carina propels businesses into the future with her data-driven approach.


Architecture, Technical Leadership, Artificial Intelligence (AI)...
Artificial Intelligence (AI), ChatGPT, OpenAI, APIs, Machine Learning...
Artificial Intelligence (AI), Python 3, Machine Learning, Software Architecture...




Preferred Environment

Python, Machine Learning, Data Science, Data Analytics, Artificial Intelligence (AI), Statistics

The most amazing...

...part of my job is using AI/ML to transform raw data into powerful insights that drive decision-making and create tangible impact for businesses and individuals.

Work Experience

AI Consultant

2023 - PRESENT
  • Devised comprehensive AI strategy roadmaps for several startups, including a consultancy, supply chain management, and digital healthcare, outlining how to leverage AI and setting specific milestones for project completion.
  • Provided detailed advice on appropriate tech stacks and AI models for various startup projects, significantly reducing development time and optimizing system performance.
  • Estimated the number of hours and the type of expertise required for AI projects, enabling startups to budget effectively and assemble the right teams.
  • Presented cutting-edge trends and possibilities in AI to stakeholders across the startup ecosystem, boosting understanding of AI capabilities and driving informed decision-making.
Technologies: Architecture, Technical Leadership, Artificial Intelligence (AI), Natural Language Processing (NLP), GPT, OpenAI GPT-4 API, OpenAI GPT-3 API, Consulting, Presentations

ML Engineer | Data Scientist | Statistician

2023 - PRESENT
  • Advised a healthcare startup on architecture and requirements for a predictive AI model.
  • Analyzed data to optimize eCommerce marketing campaigns.
  • Scraped 10+ websites, structured data, and set up automated jobs on AWS.
Technologies: Artificial Intelligence (AI), ChatGPT, OpenAI, APIs, Machine Learning, Machine Vision, Python, Data Analysis, Web Scraping, Data Scraping, Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT), Web Development, Generative Adversarial Networks (GANs), Chatbot Conversation Design, Chatbots, Computer Vision, Image Search, Statistical Analysis, Forecasting, Market Research, Jupyter Notebook, Docker, Flask, XGBoost, PyTorch, Amazon SageMaker, Quantitative Research, Data Scientist, Reports, Heatmaps, Dashboards, Hugging Face, Fine-tuning, CTO, Language Models, OpenAI GPT-4 API, OpenAI GPT-3 API, Generative Pre-trained Transformer 3 (GPT-3)

CTO and Co-founder

2023 - PRESENT
  • Designed software architecture for the company's wearable device, app, AI algorithms, and data management.
  • Developed algorithms to interpret biometric data from device sensors.
  • Set up a beta test infrastructure and launching process.
Technologies: Artificial Intelligence (AI), Python 3, Machine Learning, Software Architecture, Software, Software Design, Back-end, Data Analysis, Python, Web Development, Chatbot Conversation Design, Chatbots, Statistical Analysis, Forecasting, Market Research, Market Research & Analysis, Jupyter Notebook, Docker, Financial Modeling, Quantitative Research, CTO

Vice President, Quantitative Research

2020 - 2023
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, Software Architecture, GPT, Natural Language Processing (NLP), Generative Pre-trained Transformers (GPT), Chatbot Conversation Design, Chatbots, Statistical Analysis, Forecasting, SARIMA, LSTM, ARIMA Models, ARIMA, Jupyter Notebook, XGBoost, Stock Trading, Financial Modeling, C++, Systematic Trading, Quantitative Research, Algorithmic Trading, Data Scientist, Reports, Heatmaps, Dashboards, Language Models

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, Statistical Analysis, Forecasting, SARIMA, ARIMA Models, ARIMA, Jupyter Notebook, XGBoost, Financial Modeling, Quantitative Research, Data Scientist, Reports, Heatmaps

Social Media Marketing Web App Development
Designed and developed a web-based application that automates social media marketing efforts using generative AI. I worked with Next.js to create an intuitive, user-friendly front-end interface, ensuring a seamless user experience. Also, I developed a robust back end using Python and FastAPI and leveraged APIs from Twitter, Instagram, and LinkedIn to enable the app to interact with these platforms and automate social media marketing efforts. Finally, I incorporated the OpenAI API into the tool to utilize the power of GPT-4 for content generation, enhancing the creativity and diversity of marketing content, integrated Stripe for handling payments, and deployed the back end on AWS.

AI Strategic Roadmap Development

Created and helped implement a detailed AI strategic roadmap for several startups. My role encompassed providing strategic direction, technical expertise, and project management to drive the AI transformation journey of startups.

I conducted a thorough analysis of the startup's current systems and processes, identifying gaps and determining areas where AI could provide the most significant value. Using the startup's specific needs and goals, I provided recommendations for adopting the most suitable tech stacks and AI models. Given the critical nature of resource allocation in startups, I estimated the required person hours and the specific skill sets needed for the project's success.

Client Segmentation Algorithms

Developed algorithms to segment clients for a trading desk. The project aimed to classify clients based on unique trading behavior characteristics, enabling the bank to offer more personalized service and improve operational efficiency.

I compared a range of clustering methods, including k-means, hierarchical, and DBSCAN, among others, to ensure the most effective algorithm was selected for the segmentation task. I designed summary statistics based on high-frequency market data and higher-level client/economic data to feed into the clustering process, optimizing the accuracy and efficiency of client segmentation, and explored several dimension reduction techniques, including PCA and auto-encoders, to handle the vast amount of relevant data available. Finally, I collaborated with the business to define KPIs to monitor and measure the project's success, ensuring alignment with the bank's strategic objectives.

To wrap up the project, I wrote technical documentation and implemented the tool in production in Python. I collaborated closely with the stakeholders at the trading desk and the rest of the business.

Clinical Trial Design Statistical Analysis

Assisted a MedTech startup in designing a robust and effective clinical trial protocol, ensuring scientific validity and practical feasibility.

I calculated the necessary sample size required for the trials to provide statistically significant results, guaranteeing the trials' reliability. To understand potential outcomes and risks associated with the trial design, I ran simulations under different setups and assumptions. I created visualizations of study designs and inherent uncertainty, providing an easy-to-understand view of potential trial outcomes. Finally, I considered several statistical tests, including the t-test, analysis of variance (ANOVA), chi-squared test, Fisher's exact test, and Wilcoxon rank-sum test for the setup of the medical experiments.

FI Trade Strategies Around Market Events

Developed and backtested fixed-income trade strategies around market events based on several predictive models for market indicators. Several techniques were used, including time series modeling, copula techniques, deep learning, and reinforcement learning.

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).

Time Series Clustering for High-frequency Market Data

Research into methods and algorithms for clustering high-frequency time series data.

I retrieved the data from KDB, a high-frequency market database. Also, I investigated multiple approaches to time series clustering, such as dimensionality reduction combined with traditional clustering methods, dynamic time warping, and image-based clustering using a convolutional neural network (CNN). I executed all aspects of the project using Python.

Upon completion, I presented and delivered a detailed writeup of the project results to key stakeholders.


Python 3, Python, SQL, R, C++, CSS


LSTM, XGBoost, PyTorch, TensorFlow, Keras, React, Twitter API, LinkedIn API, Instagram API, Stripe API


Data Science, Quantitative Research, Automation


Jupyter Notebook, Ethereum, Blockchain, Docker, Microsoft, Amazon Web Services (AWS), Azure, AWS Lambda


Statistics, Probability Theory, Statistical Modeling, Data Analysis, Mathematics, Time Series Analysis, Hypothesis Testing, Data Visualization, Machine Learning, Artificial Intelligence (AI), Data Engineering, Predictive Analytics, Data Analytics, Predictive Modeling, Real-time Data, Computer Vision, Image Processing, Data Modeling, Data Reporting, Time Series, Web Scraping, Natural Language Processing (NLP), Statistical Analysis, Forecasting, SARIMA, ARIMA Models, ARIMA, Financial Modeling, Systematic Trading, Algorithmic Trading, Data Scientist, Reports, Heatmaps, Dashboards, GPT, Generative Pre-trained Transformers (GPT), Deep Learning, Bayesian Statistics, Neural Networks, Machine Vision, Data Mining, Software Architecture, APIs, Data Scraping, Web Development, Generative Adversarial Networks (GANs), Chatbot Conversation Design, Chatbots, Image Search, Market Research, Market Research & Analysis, Stock Trading, Hugging Face, Fine-tuning, CTO, Language Models, OpenAI GPT-4 API, OpenAI GPT-3 API, Generative Pre-trained Transformer 3 (GPT-3), Email, Google Colaboratory (Colab), Business, Finance, Financial Markets, Business Psychology, Marketing Mix, Mechanics, Presentations, Technical Writing, Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNN), Image Recognition, Cloud, Copula, Deep Reinforcement Learning, Software, Software Design, Back-end, ChatGPT, OpenAI, Color Theory, Color Science, Architecture, Technical Leadership, Consulting, Bloom, Pinecone, SaaS, Clustering, K-means Clustering, Hierarchical Clustering, Variational Autoencoders, Principal Component Analysis (PCA), Dimensionality Reduction, Long Short-term Memory (LSTM), FastAPI, Analysis of Variance (ANOVA), T-test, Simulations, Clinical Trials


Flask, Next.js


Visual Studio, Tableau, Amazon SageMaker, PyCharm, Bitbucket, Slack, Skype, Git, GitHub, LaTeX, Jira


MongoDB, Google Cloud, Kdb+

2016 - 2018

Master's Degree in Applied Mathematics

Delft University of Technology - Delft, The Netherlands

2012 - 2016

Bachelor's Degree in Business Administration

Erasmus University Rotterdam - Rotterdam, The Netherlands

2011 - 2016

Bachelor's Degree in Engineering

Delft University of Technology - Delft, The Netherlands


Building with Large Language Models



Deep Learning


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