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Jack Staunton

Jack Staunton

Graph Data Scientist II

Redhorse Corporation

Technologies

My Portfolio Highlights

My New Track

SQL Fundamentals

My New Course

Supervised Learning with scikit-learn

My New Track

SQL Fundamentals

Data painter, using visualization to bring insights to life.

My Work

Take a look at my latest work.

course

Data Manipulation in SQL

course

Unsupervised Learning in Python

course

Supervised Learning with scikit-learn

course

Data Manipulation in SQL

DataCamp Course Completion

Take a look at all the courses I’ve completed on DataCamp.

Courses

Supervised Learning with scikit-learn
Data Manipulation in SQL
PostgreSQL Summary Stats and Window Functions
Functions for Manipulating Data in PostgreSQL

My Work Experience

Where I've interned and worked during my career.

Redhorse Corporation | Jan 2023 - Present

Graph Data Scientist II

Work in cross-functional Agile team with platform engineers, full stack engineers and developers, data and graph engineers, other data scientists, and intelligence analysts with subject matter expertise in threat finance. Work with global scale datasets represented as knowledge graphs in neo4j databases, developing queries in cypher, actions in Hume, and analyses in other tools like GDS library, DGL, pyG, etc. to support analyst and customer needs.
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NNData | Sep 2019 - Nov 2022

Senior Data Scientist

Natural Language Processing; Named Entity Recognition; Named Entity Linking; Graph Analytics; Composable Embedded Systems; Multi Domain Analytics.

NNData | Apr 2021 - Aug 2022

Consultant - Security and Threat Verification; Global Security Shared Services.

N/A

NNData | Nov 2020 - Dec 2021

Principal Investigator - Rapid Multimodal Communications (DARPA SBIR)

Collapse of DNA in ac Electric Fields Mismatch in Mechanical and Adhesive Properties Induces Pulsating Cancer Cell Migration in Epithelial Monolayer Correlating confocal microscopy and atomic force indentation reveals metastatic cancer cells stiffen during invasion into collagen I matrices Washington DC-Baltimore Area We have designed a prototype Virtual Reality platform (leveraging consumer- grade hardware and exploits the fertile ecosystem of digital assets generated in the gaming industry) that provides immersive human-machine and human- human interaction experiences with complex high-dimensional data to support data-driven executive decision-making.

The Data Incubator | Jun 2019 - Aug 2019

Data Science Fellow

The Data Incubator is a Cornell-funded data science training organization. The Data Science Fellowship is a highly selective, advanced and intensive 8 week data science bootcamp admitting only the top 2% of 8000+ applicants per cohort. The curriculum is project based but has a stronger emphasis on classroom lecture and instruction than e.g. Insight, with daily lectures and coding challenges. Weekly miniprojects focused on Data Wrangling, Machine Learning, Natural Language Processing, Time Series Analysis, Production, Visualization, Distributed Computing, Relational Databases, and Artificial Neural Networks. Capstone Project: Bots 4 Humans: An Interactive Web Application to Craft, Trade and Deploy Your Own Algorithm for Trading Financial Instruments Techniques and Technologies: SQL, SQLite3, sqlchemy, Spark, pyspark, word2vec, BeautifulSoup, spacy, Git version control, JupyterLab, python, pandas, datetime, io, gzip, json, functools, itertools, collections, numpy, scipy, tensorflow, scikit-learn, Flask, Bokeh, matplotlib, seaborn, statsmodels, pyramid-arima, TA-Lib, requests, requests-futures, FRED, alpha-vantage, Quandl, Logistic Regression, Nearest Neighbors, Decision Tree, AdaBoost, Naive Bayes, QDA, Linear SVM, Gradient Boosting Classifier, Gaussian Process, Random Forest, and Neural Networks, regression, classification, time complexity analysis, time series analysis, ARIMA, SARIMAX, etc.

The National Institutes of Health | Feb 2015 - Jan 2019

CRTA Postdoctoral Fellow

Project: Interrogated the complex interplay between metastatic cancer cells and surrounding tissue in the context of mechanical properties at the micrometer length scale and picoNewton force scale relevant to cell motility and invasion; advanced the state of the art in 3D force spectroscopy by developing and applying new methods in optical trapping for in vivo specimens; identified novel dynamical scaling relationships in the power law rheology of cells and hydrogels over a broad band of frequencies in the kHz range.

National Cancer Institute (NCI) | Oct 2009 - Dec 2014

PSOC Trainee, Physical Sciences - Oncology Centers Network

The first generation of the National Cancer Institute's Physical Sciences - Oncology Centers (PS-OC) Network brought physical science researchers from STEM disciplines into the fray to work closely with clinical investigators to approach cancer from a new perspective. As a graduate student I was heavily engaged as a participating member in this nationwide consortium from its inception to its conclusion. I participated in a variety of workshops, delivered numerous oral and visual presentations of my research, and interacted with other researchers of all ranks from across the country on large collaborative projects.

Arizona State University | Sep 2009 - Dec 2014

Graduate Research Associate

Project: To address the question of what makes cancerous cells softer and elucidate the mechanical interactions between the cell and its microenvironment, I combine AFM nanoindentation and optical fluorescence techniques to investigate the mechanical properties of eukaryotic cells embedded in 3D matrices such as collagen or Matrigel.

Arizona State University | Aug 2009 - Dec 2014

Graduate Teaching Associate

N/A

U.S. Department of Education | Jan 2011 - Dec 2012

GAANN Fellow

As a recipient of the Department of Education's GAANN Fellowship, I redesigned and deployed a new curriculum for a class module on Helmholtz coils in an Honors undergraduate Laboratory course on Electricity and Magnetism in the Arizona State University Department of Physics, under faculty supervision. As a GAANN Fellow I participated in a 6 week summer workshop for physics educators oriented around the Modeling Instruction pedagogy, which organizes a course around a small number of scientific models, thus making the course coherent. In development since 1990 under the leadership of David Hestenes (Emeritus Professor of Physics, Arizona State University), Modeling Instruction applies structured inquiry techniques to the teaching of basic skills and practices in mathematical modeling, proportional reasoning, quantitative estimation and technology-enabled data collection and analysis.

North Carolina State University | Oct 2007 - May 2009

Undergraduate Research Assistant

Project: Prove concept for a microfluidics-based device for electronic sequencing of DNA. Lyse E.coli cells in microchannel on a micro/nanofluidic chip, isolate the nuclear DNA using electrophoresis, and use electric bias to confine the DNA in 50 nm-wide nanochannels.

My Education

Take a look at my formal education

Ph.D. in Physics (summa cum laude)Arizona State University | 2014
M.S. in PhysicsArizona State University | 2011
B.S. in Philosophy (Logic, Representation & Reasoning)North Carolina State University | 2009
B.S. in Physics (Minor: Mathematics)North Carolina State University | 2009
A.S. in SciencesWake Technical Community College | 2006

About Me

Jack Staunton

PhD Physicist and former Cancer Research Fellow at National Cancer Institute, now doing data science (100% remote).

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