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LinkedIn
DAVID YERRINGTON
linkedin.com/in/davidyerrington
Mobile
DATA SCIENTIST / ENGINEER
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Email
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SUMMARY
PROGRAMMING
Self-taught engineer with 15+ years experience leading teams and
building innovative products for humans. Strong knowledge of
statistical data analysis and machine learning techniques, having
authored and taught curriculum for one of the leading data science
boot camps.
Python, Scala / Java, SQL, Golang,
Javascript, Bash / Shell
I help companies define specific, actionable outcomes with data
from vague requirements, then build reproducible work from
analysis to working deployments. Recently, I was chief data officer
at Bluwhale, where I lead a team in defining the methodology for
data science projects for some of the world's biggest game
companies while integrating our work into a product that automated
common analysis tasks.
Specialties:
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Scientific Python
Data visualization (matplotlib, bokeh, dashboard development)
SDLC methodologies and management
Educational data science curriculum development
Enterprise level application design and development
Pipeline development for big data applications (ETL)
Machine learning theory and applications in predictive analysis
Restful services architecture
PLATFORMS / APPLICATIONS / APIs
ML – scikit-learn, Keras, Tensorflow
Python – Pandas, Numpy, Scipy
NLP – Gensim, Spacy, NLTK
Spark – Pyspark / Scala
AWS – EMR, EC2, S3, Redshift
GPC – CloudGPU, BigQuery, Cloud Build,
Kubernetes
DataViz – matplotlib, bokeh, seaborn, etc.
Backend – Django, Flask, Play
RDBMS – Postgres, MySQL, BigQuery,
Redshift, Hive, MongoDB
DOMAIN EXPERTISE
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EDUCATION
2014
Data Science
General Assembly, San Francisco
2014
Machine Learning- Certificate
Stanford Extension
1999
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Recommender system
development
NLP / topic modeling
Parametric modeling
Neural networks
Mobile / Games Analytics / BI
Technical instruction
ML deployment
Music Performance / Modern Theory
University of Alaska Anchorage
AWARDS
Data For Diplomas Competition,
AT&T
Top Finalist
3rd Place / 2015
RESUME
EMPLOYMENT
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19’ April-Nov Bluwhale Inc.
Chief Data Officer
Primarily focused on scoping of data science projects, including:
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Experiment design
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Deployment and management of production machine learning systems
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Supporting company product team with new client insights
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Rapid-prototyping of data-driven prototypes before platform integration
Responsible for scoping and implementation of infrastructure supporting data acquisition channels for
new clients involving ETL, data quality, and sustaining service level agreements.
Developed analysis methodology for team projects focused on multiple mobile gaming franchises that
addressed sampling, baselines, evaluation metrics, reproducibility, and model remediation. Guided the
weekly presentation of team progress from analysis of client data, and prototype ML applications that
identified game events related to churn, conversion(s), and game economics driving in-app-purchases.
Actively interviewed candidates across the company for design, engineering, DevOps, BI, and data
science roles.
Tools Development: Custom dashboards, model remediation / online validation monitoring, automated
feature engineering, automated experiments.
Environment: Google cloud Services, BigQuery, Postgres, Google Collab, Kubernetes, Cloudbuild,
Spark/PySpark, Dask, MLFlow, scikit-learn, Airflow, Featuretools, Pyviz Panel, Holoviews, JuptyerHub.
Programming: Python, Javascript, Scala, SQL, Bash
Accomplishments:
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Created first prototype wireframes and lead technical implementation of data ingestion, model
assets, and backend services for 1st web product prototype that lead the company to seed
funding and new client engagements.
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Mentored small team to basic competency with Python, Pandas, and Numpy to help with
analysis and data handling for ETL, EDA, and basic development supporting data related
projects.
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I lead the development of a highly modular library for experiment evaluation, deployment, and
plotting that powered many aspects of our day to day work. This library cut nearly 50% of our
time to evaluate sampling, the confidence of model parameters, reporting of data issues, and
deployment of successful ideas into production.
PLAY
WORK
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General Assembly
Global Lead Data Science Instructor
Implemented mock-ups using grid frameworks and designed websites using CSS, XHTML and
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General Assembly
Lead Global Data Science Instructor
A key contributor to content taught within global organization related to data science pilot programs and
curriculum including machine learning, statistics, math, engineering, and their applications. Working with
stakeholders to help develop the internal and student-facing lectures, labs, and project material based
on learning objectives and market research with job placement outcomes in mind. My role was split
between research and development, development of content, in-class instructor support, lecturing on
data science topics, and consulting for scope and methodology of final student projects.
Planning and delivering lectures to the North American market covering ten major metropolitan regions,
in a hybrid in-class and online format. Supporting daily team operations.
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Successfully piloted 3 major programs with baseline content now actively taught within
organization, worldwide
Development pilot DSI programs, now offered world-wide
Lectures on machine learning, statistics, and engineering topics
Curriculum and lecture development
Consulted 1000s of final projects leading students to careers as data scientists, analysts,
and various roles in the data science job market
Chief editor of scientific Python stack + big data tools curriculum
Collaborated with global curriculum developers as senior member of advisory board
Her (weareher.com / YC)
Data Scientist
Lead role in recommender systems research and development, defining core metrics for success, and
corresponding production resources with EMR/AWS. A/B experimental design and analysis.
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Exploratory analysis + reporting metrics
Comprehensive database management and SQL development
Data pipeline planning and design
Backend integration development with Scala and Golang
Feature engineering/ETL supporting user-based collaborative recommender systems
Hiring / interviewing of engineering and analyst resources
