Matthew Mitsui
Verified Expert in Engineering
Data Science Developer
New York City, NY, United States
Toptal member since November 30, 2017
Matthew is a diligent data scientist with over eight years of experience in machine learning, research, statistics, natural language processing, behavioral modeling, and software development. He helps companies build data-driven products to analyze user behavior and enable users to drive their brands and success.
Portfolio
Experience
- Python - 10 years
- Data Science - 8 years
- Scikit-learn - 6 years
- Jupyter Notebook - 5 years
- NumPy - 5 years
- Pandas - 5 years
- Asana - 4 years
- TensorFlow - 2 years
Work Experience
Head of Data Research
VidIQ
- Performed data science and data analysis individual contributor duties for a tech startup.
- Developed a YouTube video title recommender system for over two million creators.
- Developed a regression model of YouTube search traffic for millions of daily keywords.
- Expanded search traffic and video idea product coverage by up to 50% of corner cases.
- Aggregated daily trends of popular sounds in TikTok for 50K+ users of the TikTok app.
- Communicated results with managers, technical stakeholders, and content creators.
- Assisted in hiring and onboarded five new data scientists.
- Executed Agile and Waterfall projects with engineers and fellow data scientists.
Python and GraphQL Middleware API Engineer
Digitalware, Inc.
- Wrote APIs and data handlers for various product platforms.
- Designed and implemented data parsers for data ingestion.
- Wrote APIs and services using JavaScript, Python, and Django.
Postdoctoral Associate
Rutgers University
- Predicted problems encountered by web searchers using supervised learning.
- Designed a master's level course in research methods, teaching statistics and R in the library and information science department.
- Assisted with grant writing on emerging big data infrastructure, deep learning, bias in information retrieval, and explainable recommendations.
- Mentored research projects of undergraduate and graduate students.
Graduate Student Research Assistant
Rutgers University
- Predicted searcher intentions from web search patterns, improving accuracy by 1.5-8x over naïve baseline with logistic regression.
- Mapped relationships between searcher demographics, search behaviors, and their search tasks using structural equation modeling, improving six of seven goodness-of-fit metrics.
- Developed a structured learning approach to discover unknown relationships between searcher characteristics, search tasks, and behavior.
- Designed a user-friendly interface to collect web browsing data using Python, HTML, and JavaScript in a Model-View-Controller framework.
- Extracted crowd annotations of search logs using Amazon Mechanical Turk.
Teaching Assistant
Rutgers University
- Engaged undergraduate students in Computer Science courses.
- Served as a teaching assistant for an undergraduate algorithm course for one year.
- Acted as a teaching assistant for an undergraduate course in C programming for one year.
- Held regular office hours on weekly bases for each course.
- Assisted in the grading and designing of tests, periodic homework assignments, and group projects.
Graduate Research Fellow
Rutgers University
- Attended regular multidisciplinary seminars intersecting computer science and psychology.
- Involved in multidisciplinary coursework intersecting the aforementioned fields.
- Took part in research in computer graphics regularly.
- Engaged in coursework required by the computer science curriculum as required by my fellowship.
Computer Science Intern
National Security Agency
- Participated in a 12-week internship program for computer science.
- Contributed to an NSA's mission through the project.
- Completed a technical paper as part of the project.
- Worked in a collaborative group with a senior project on the project.
Education
Ph.D. Degree in Computer Science
Rutgers University - New Brunswick, NJ, USA
Bachelor of Science Degree in Computer Science
Rutgers University - New Brunswick, NJ, USA
Certifications
Neural Networks and Deep Learning
Coursera
Bayesian Statistics
Coursera
Skills
Libraries/APIs
Pandas, Scikit-learn, jQuery, NumPy, Matplotlib, Natural Language Toolkit (NLTK), SciPy, TensorFlow, Keras
Tools
PyCharm, PhpStorm, Jupyter, Asana, Sequel Pro, GitHub, Terminal, Git, Sisense, LaTeX
Languages
Python 3, Python 2, JavaScript, Python, SQL, PHP 5, R, PHP, C, Java
Paradigms
Object-oriented Programming (OOP), REST
Platforms
MacOS, Jupyter Notebook, OS X, Amazon Web Services (AWS), Linux, Amazon EC2, Docker
Storage
MySQL, SQLite, Redshift
Frameworks
Bootstrap, Laravel, Django, Spark
Other
Writing & Editing, Data Structures, Data Science, Regression, Unsupervised Learning, Supervised Learning, Data Analysis, Recommendation Systems, Natural Language Processing (NLP), Data Visualization, Statistics, Data Analytics, Predictive Modeling, Machine Learning, Algorithms, Statistical Data Analysis, Generative Pre-trained Transformers (GPT), SFTP, SSH, Eye Tracking, Deep Learning, Statistical Analysis, Neural Networks, Bayesian Statistics, Time Series Analysis
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