My Résumé
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Gus Lipkin
What Drives Me
I’ve always loved asking ‘how?’ and ‘why?’ Since starting my journey as a data scientist, I’ve been able to answer ‘how?’ by developing tools to support my teammates, while answering ‘why?’ with analyses to support data driven decision making. I’m looking for a position where I can build a career using my skills to help my team and conduct meaningful analyses that inform business decisions and contribute to achieving company goals.
Experience
Data Scientist – Lander Analytics
- Build and maintain data science infrastructure with Docker, Kubernetes, GitHub Actions, and Ansible Playbooks according to customer needs and design specifications
- Construct rigorous analyses in R and thorough and interactive reports and dashboards using Shiny for R
- Bring the joys of R and data science to others through tailored workshops and talks at conferences
Data Analyst – Publix Super Markets
- Develop novel analyses and models to provide key insights to business stakeholders including store managers
- Build and maintain internal R packages to aid in analysis such as ‘publixdate’ for working with Publix’s system of dates or ‘pubsub’ for general utilities and a streamlined database connection interface
- Seek out and participate in strategic initiatives which require analytic support from across corporate
- Visualize data and create reports in Power BI to display model performance and facilitate data-driven decisions
Data Science Project Team Lead – Tallahassee Memorial Healthcare
- Correlate patient feedback to readmissions and patient experience using linear regression and decision trees
- Create an interactive training tool for nurses using results found in the analysis with HTML and JavaScript
- Work with capstone sponsor to define project timeline and goals and author a report on project findings
Projects
Shrink Narrative Reports – Publix Super Markets
- Built a fully automated reporting pipeline with R and Python in for Spark in a Databricks environment that delivers monthly PDF reports to all Publix stores to support goals to reduce retail shrink
- Analyzes store shrink metrics and provides actionable insights through targeted operations suggestions
- Built and implemented a SQL translation function leveraging the tidyverse, dbplyr, and sparklyr to expedite writing new targeted operations suggestions as operations leaders see demand
- Completed the project four months ahead of schedule and saved $85k per year in contracting costs
Store/Item Activation Recommendations – Publix Super Markets
- Implemented a machine learning recommendation system to optimize store/item availability combinations
- Accepts any combination of stores and items and imputes data for missing combinations
- Uses the tidymodels suite to cluster stores based on similar latent features from the recommendation process
- Pioneered “project as a package” for easier documentation, maintenance, legibility, requirements, and usability
Education
– Bachelor of Science, Business Analytics with concentrations in Quantitative Economics & Econometrics and Intelligent Mobility
– Associate of Arts