ALDERIK VAN DER HEYDE

Middlebury College Graduate, Coder, Crypto Enthusiast, Lacrosse Player, San Diegan, Surfer, Snowboarder

You can find my personal information below as well as links to my LinkedIn, Github, and resumé!

  • San Diego & Middlebury
About Me

Hi! My name is Alderik van der Heyde.

I'm a Trade Ops Engineer at Flow Traders. I have gained strong DevOps experience throughout the past year with exposure to tools like ansible, Ansible, Kubernetes, Bash, Linux, Docker, Prometheus, Grafana.io. Check out my resumé, GitHub, and LinkedIn (all linked to the bottom left) to see what I've done!

My personal interests include lacrosse, personal investing, snowboard, surfing, fantasy football and cryptocurrency.

Projects

Major projects during College

Covid-19 Open Reserach Dataset Challenge

Python

Conducted natural-language processing on a corpus of research papers on corona virus to answer question about the virus.

Exploratory Data Analysis of Airline Flights Dataset

Python

Explored a dataset of data on every domestic flight in the United States.

Kaggle NFL Big Data Bowl

Python

Built off pre-existing entries to make a model to predict the amount of yards earned on a given play.

Alpha Factor Research and Backtesting

Python

Developed alpha factors to attempt to make a model that could predict financial markets movements. Backtested trading algorithms on Quantopian.

Machine Learning Model that Predicts Genetic Variants

Python

Constructed multiple machine-learning models aimed at identifying structural genetic variants. Adapted new variant identification features from literature to create images of genetic reads for classification. Improved accuracy by tuning hyperparameters, stacking models, plotting learning curves, using k-folds cross validation

Experience

An overview of my previous professional experiences.

Present

Trade Operations @ Flow Traders

Developed reliable monitoring for services and hosts using Prometheus metrics and Grafana for alerts. Automated with python and bash scripts: daily processes and repetitive tasks the create toil for the team. Managed deployments with ansible and incident rotations with no significant outages despite critical incidents.

   New York, NY
   Present
Summer 2021

Technology Intern @ Wells Fargo

Conducted unsupervised machine learning to cluster similar issues to create a reference for remediation of new issues. Used natural language processing techniques to calculate similarity scores of inputs to provide feedback on the input. Developed an enhanced search tool for finding desired documents in corpus based on keyword matching.

  Remote (San Diego, CA)
   June — August 2021
Fall 2020

Data Science Intern @ Qsemble Capital

Conducted exploratory data analysis, using matplotlib and seaborn, on datasets relevant to alpha factor research. Created and back tested alpha factors using Pandas and NumPy to replicate results of academic research. Integrated alpha factors to trading universe and calendar in order to be deployable in predicting stock returns

  Remote (New York, NY)
   September — December 2020
Summer 2020

Undergraduate Research Assistant

Constructed multiple machine-learning models aimed at identifying structural genetic variants. Adapted new variant identification features from literature to create images of genetic reads for classification. Improved accuracy by tuning hyperparameters, stacking models, plotting learning curves, using k-folds cross validation

  Remote (Middlebury, VT)
   May — August 2020
Summer 2019

Personal Project - Quantitative Finance Research

Developed my own systematic trading algorithm that utilizes alpha factors from academic papers and personal research. Used python for individual alpha factor discovery and data analysis of the factors’ strength of signal. Back tested algorithm using historical market data through Quantopian’s API

   San Diego, CA
   May — August 2019
Summer 2018

Finance and Accounting Intern

Built financial valuation models specified by the CFO for the board to use to present to Venture Capital firms. Recorded daily business transactions into NetSuite by analyzing and creating journal entries

  San Diego, CA
   May - August 2018

Skills

All the languages, frameworks, libraries and technologies I've worked with.

Python

Kubernetes

Prometheus

Pandas

Grafana

HTML

CSS

SQL

Git

Kafka

bash

Numpy

Matplotlib

Keras

Seaborn

SciPy

Scikit Learn

Ansible

Education

My academic background.

Middlebury College

Bachelor of Arts, Computer Science with interdisciplinary in Data Science

GPA: 3.7

Relevant Completed Coursework:

  • MATH218: Statistical Learning
  • CSCI312: Software Development
  • CS701: CS Senior Seminar
  • CS451: Machine Learning
  • CS302: Algorithms and Complexity
  • CS202: Computer Architecture
  • CS200: Math Foundations
  • CS201: Data Structures
  • CS101: Intro to Computing
  • MATH311: Statistics
  • MATH216: Introduction to Data Science
  • MATH200: Linear Algebra
  • ECON210: Econ Stats
  • INTD1212: Statistical Models of the Stock Market

DIS Study Abroad

Fall 2019

Relevant Coursework:

  • Artificial Intelligence
  • Neural Networks
  • Big Data
  • International Financial Management
  • Danish