Alexander Graber

Languages

Proficient with Python (pandas, numpy, scikit-learn), R (tidyverse), SQL, bash

Platforms

Experience with Git, Tableau, Docker, Kubernetes, Azure, Microsoft Office

Techniques

Forecasting, Recommendations, NLP & Topic Models, Clustering, Classification, Regression, Tree-based methods

Leadership & Management

Technical leadership and training as demonstrated by defining SOPs and providing trainings, mentoring junior team members, and managing contract employees

Communication

Adept at communicating data science concepts & outcomes to business stakeholders; Technical documentation

Others Skill

Collaboration, Problem solving, using Google/Github/Stack Overflow/Reddit

Project Management Institute (PMI)

Data Scientist, Data Scientist II • Apr 2019 - Current

• Designed and lead deployment of MLOps infrastructure and tooling, and integration with deployed models and workflows.
• Collaboratively developed internal feature store by collaboratively guiding development of analytics data pipelines with direct integrations to/from deployed models.
• Developed and published internal Python packages to standardize data science functions, empower faster experimentation & deployment, and reduce code recycling/technical debt.
• Developed and delivered 2 internal “data products” across the complete ML lifecycle (automated forecasting, recommendation); supported development of 4 others (Churn, CLV, Segmentation, Visit Intention).
• Managed/mentored junior Data Scientists and contractors; defined and set code quality standards & encouraged best practices (testing, ci/cd, code reviews) across data team projects.

GS Shop

Independent Machine Learning Contractor • Q4 2018

• Developed recommendation engine package in R in 3 weeks. Package supplied recommendations for each of >8 million users for each of >51k products using 2 prediction methods - Logistic Regression with Elastic Net Regularization and SVD-based Collaborative Filtering.

Zappos.com

Data Analytics Intern, Data Science • Jun, 2018 — Aug, 2018

• Developed forecasting package in R, including parallelized forecasting, error calculation, and validation functions.
• Validated forecasts; financial forecast validation indicate forecasting package capable of 90% forecasting accuracy.

RG+A

Sr. Manager, Marketing Science • Nov, 2016 — Dec, 2018

• Implemented new analysis and reporting technique allowing novel understanding and visualization of the treatment flow in simulated prescribing decisions through use of Sankey Diagrams.
• Created Excel-based share simulator, providing single tool for client instead of innumerable reports.

Léger

Account Manager • Oct, 2014 — Nov, 2016

• Prevented loss of client by revitalizing Messaging/Sales-Force Effectiveness Tracker through improved analyses and reporting.
• Managed market research in multiple verticals (Biopharma, OTC Healthcare, CPG, Gaming, Travel/Leisure) from kickoff to presentation, including questionnaire development, analysis, report development, and presentation.

RG+A

Various • Aug, 2006 — Sept, 2014

• Research Manager
• Research Analyst
• Desktop Engineer

Drexel University, LeBow College of Business

Master of Science, Business Analytics • 2017 — 2019

• Modeling Concentration
• 4.0 GPA

Focus on Data Science Algorithms, Analytics, and Interpretation

Bowdoin College

Bachelor of Arts • 2005 — 2009

• Major - International Relations
• Major - Comparative Religion
• Minor - Computer Science

Dual major + minor, varsity athlete, club sport leader

Perkiomen Valley High School

High School Diploma • 2005

Machine Learning

Coursera / Stanford • 2018

Completed Andrew Ng's Machine Learning MOOC on Coursera.

Graphic Design Specialization

Coursera / CalArts • 2016

Completed multi-course Graphics Design Specialization MOOC on Coursera.

• Homelab - bare metal k8s cluster running self-hosted services
• Computers & technology - watercooled PC, custom keyboard(s), cyberdeck
• Endurance sports (triathlons, (half)marathons)
• Tinkering, DIY
• Music (violinist)

• LinkedIn
• Github repositories