Daniel Burkhardt Cerigo
Verified Expert in Engineering
Machine Learning Developer
With over four years of experience under his belt, Daniel is a detail-oriented data scientist specializing in predictive modeling and optimization via reinforcement learning. Along with evident leadership and communication skills (proven in his role as a chairperson for an international peace-education nonprofit), he’s driven to create measurable impact for organizations. Daniel also has a master’s degree in physics and philosophy from Oxford.
Git, Unix, Linux
The most amazing...
...thing I’ve built was an online-reinforcement-learning platform optimizing the product pricing of a large travel company, operating on revenue in the millions.
Machine Learning Consultant
- Consulted on data valuing for a UK government's civil service organization, the Office of Rail & Road; advised on how to best leverage their data and viable use cases of automated decision making and machine learning.
- Built POC machine -earning/probabilistic models with an interface through an interactive dashboard.
- Ensured the deployment of the entire system easy for the organization's employees.
- Implemented natural language processing on vast numbers of daily logs and made the insights accessible to employees through an interactive dashboard.
- Consulted with senior executives on project scope, timelines, and expected outcomes.
- Researched about state-of-the-art reinforcement learning techniques for pricing optimization.
- Automated decision-making directly affecting the top and bottom-line performance of the company.
- Built a platform for the orchestration, reporting, and maintenance of online learning pricing algorithms.
- Developed an extensive and flexible interactive dashboard for a pricing optimization platform used by business members outside of data science.
- Worked as part of the revenue management team.
- Communicated with business stakeholders.
Senior Data Engineer
Blue Vision Labs
- Deployed and maintained large-scale data collection operations across the UK and US; this included the hiring, onboarding, and management of data collection operatives.
- Built and deployed automated data quality assurance and data reporting pipelines.
- Curated interactive visualizations and analytical reports on the status of the company's data for investors and clients.
Machine Learning Scientist
- Built models using gradient boosting/random forests/deep learning with a heavy emphasis on time-series geospatial data, combining multiple diverse data streams into features.
Data Scientist | Back-end Developer
- Built fully automated crawling systems using Docker, Cassandra, Python, and PostgreSQL.
- Deployed with Ansible.
- Automated raw data processing.
- Developed various ML frameworks for modeling and predictive analytics on top of this raw data.
Santa Fe Institute
- Performed complex modeling and analysis of a terabyte-sized dataset of patents to gain insights into the process of technological innovation.
Institute for New Economic Thinking — University of Oxford
- Analyzed a corpus of patent data through advance means to publish in EPJ Data Science journal: “Understanding Technological Change from the Map of Capabilities.”.
Online Reinforcement-learning Platform
The company's revenue was in the millions and this platform generated measurable uplifts (double figures range) in the top line, bottom line, and conversions. My platform included the ability for organization members to configure and deploy new optimization algorithms on subsections of traffic. I also provided a fully customized dashboard app for the hourly tracking of metrics, with the ability to deep-dive into the algorithm behaviors and outputs for explainability, debugging, and further algorithm development.
Pandas, NumPy, PyMC, TensorFlow, Keras, Matplotlib, REST APIs, NetworkX, Natural Language Toolkit (NLTK), Scikit-learn
Data Science, Unit Testing, Scrum, Agile, Test-driven Development (TDD)
Machine Learning, Reinforcement Learning, Optimization, Bayesian Inference & Modeling, Bayesian Statistics, Deep Learning, Gunicorn, APIs, Learning, Unit, Dash, Dashboards
Python, SQL, Bash
Git, Vim Text Editor, Ansible, NGINX, Plotly, LaTeX
Amazon Web Services (AWS), Docker, Jupyter Notebook, Linux, Unix, MacOS, Google Cloud Platform (GCP)
PostgreSQL, MySQL, SQLite, PostGIS, Cassandra, Redshift
Master's Degree in Physics and Philosophy
University of Oxford - Oxford, UK
Stanford University via Coursera