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.
Portfolio
Experience
- Data Visualization - 10 years
- Statistics - 7 years
- Data Analysis - 7 years
- Mathematics - 7 years
- Probability Theory - 7 years
- Time Series Analysis - 7 years
- Python 3 - 6 years
- Deep Learning - 5 years
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
Freelance
- 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.
ML Engineer | Data Scientist | Statistician
Freelance
- 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.
Co-founder & Head of Science & Technology
JawSense
- Designed software architecture for the company's wearable device, app, AI algorithms, and data management.
- Oversaw and co-developed several mobile and PC apps for internal and external purposes.
- Contributed to clinical trial protocols, power calculations, grant applications, and QMS.
- Developed algorithms to interpret biometric data from device sensors.
Vice President, Quantitative Research
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.
Quantitative Analyst
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.
Experience
Social Media Marketing Web App Development
http://www.socialbob.aiAI Strategic Roadmap Development
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
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
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
Predictive Model for Mortgage Prepayment Rates
Multivariate Timeseries Prediction for Cryptocurrencies
Time Series Clustering for High-frequency Market 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.
Education
Master's Degree in Applied Mathematics
Delft University of Technology - Delft, The Netherlands
Bachelor's Degree in Business Administration
Erasmus University Rotterdam - Rotterdam, The Netherlands
Bachelor's Degree in Engineering
Delft University of Technology - Delft, The Netherlands
Certifications
Building with Large Language Models
FourthBrain
Deep Learning
Coursera
Skills
Libraries/APIs
LSTM, XGBoost, Beautiful Soup, PyTorch, Claude API, OpenCV, TensorFlow, Keras, React, X (formerly Twitter) API, LinkedIn API, Instagram API, Stripe API
Tools
GitHub, SARIMA, ARIMA, Claude, Visual Studio, Tableau, Amazon SageMaker, Whisper, Claude Code, AutoCAD, PyCharm, Bitbucket, Slack, Skype, Git, LaTeX, Jira, ChatGPT
Languages
Python 3, Python, SQL, R, C++, CSS
Paradigms
Quantitative Research, HIPAA Compliance, UI Design, UX Design, Automation
Platforms
Jupyter Notebook, Amazon Web Services (AWS), Ethereum, Blockchain, Docker, Google Cloud Platform (GCP), Microsoft, Azure, AWS Lambda
Storage
JSON, MongoDB, Google Cloud, PostgreSQL, Kdb+
Frameworks
Flask, LangGraph, Next.js
Industry Expertise
Healthcare
Other
Statistics, Probability Theory, Statistical Modeling, Data Analysis, Mathematics, Time Series Analysis, Hypothesis Testing, Data Visualization, Machine Learning, Data Science, Artificial Intelligence (AI), Data Engineering, Predictive Analytics, Data Analytics, Predictive Modeling, Real-time Data, Computer Vision, Image Processing, Data Modeling, Data Reporting, Time Series, Software Architecture, Web Scraping, Natural Language Processing (NLP), Statistical Analysis, Forecasting, Financial Modeling, Systematic Trading, Algorithmic Trading, Data Scientist, Reports, Heatmaps, Dashboards, Generative Pre-trained Transformers (GPT), Technical Leadership, Model Evaluation, AI Agents, AI Engineering, Large Language Models (LLMs), AI Modeling, Open-source LLMs, Prompt Engineering, Algorithms, Datasets, Risk Models, Documentation, Large Data Sets, Data Preprocessing, AI Architecture, Communication, Technical Consulting, Generative Artificial Intelligence (GenAI), Regression, Analytics, Deep Learning, Bayesian Statistics, Neural Networks, Machine Vision, Data Mining, 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), FastAPI, Technical Architecture, HIPAA, Retrieval-augmented Generation (RAG), Leadership, Agentic AI Systems, Agentic RAG Systems, Agentic Workflow Design, RAG Architecture, LangChain, Speech-to-Text (STT), Startups, Small Language Models (SLMs), Trading, Credit Risk, Solution Design, Agentic AI, AI Avatars, User Experience (UX), RAG Systems, Economics, Text Analytics, Email, Google Colaboratory (Colab), Business, Finance, Financial Markets, Business Psychology, Marketing Mix, Mechanics, Presentations, Technical Writing, Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), Image Recognition, Cloud, Copula, Deep Reinforcement Learning, Software, Software Design, Back-end, OpenAI, Color Theory, Color Science, Architecture, Consulting, Bloom, Pinecone, SaaS, Clustering, K-means Clustering, Hierarchical Clustering, Variational Autoencoders (VAEs), Principal Component Analysis (PCA), Dimensionality Reduction, Long Short-term Memory (LSTM), Analysis of Variance (ANOVA), T-test, Simulations, Clinical Trials, General Data Protection Regulation (GDPR), FDA, Actuarial
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