Adam Butcher

Senior Associate - Data and Analytics @ Infosys

About

I'm a data scientist with 4+ years of experience who has: • Led end-to-end analysis of 4,000+ patient records using Python and PCA to identify key obesity predictors, presenting actionable insights to 150+ stakeholders and aligning project scope with business objectives. • Streamlined 400+ variable names across a 10TB database by mapping SQL schema in Excel and refactoring Python/SQL scripts, enhancing data clarity, consistency, and cross-team collaboration with zero downtime. Proficient in: Python, SQL, Machine Learning

Country

United States

City

Plano

Industry

Computer Software

Skill

Data Analysis, Python, SQL, Google Cloud Platform (GCP), MySQL, Mathematics, Project Management, Machine Learning, Statistics, Data Science, Java, Microsoft Office, C++, Windows, Microsoft Excel, R, Eclipse, Visual Studio, Tableau, MongoDB

Experience

Senior Associate - Data and Analytics

Infosys

2023-1 - 2024-11 · 1 yr 11 mos

Richardson, Texas

• Designed and implemented an ETL pipeline for a major telecommunications company to ingest and migrate 20+ CSV and DAT files into a GCP Bucket, streamlining data processing. • Loaded and transformed data in BigQuery, creating ~100 optimized tables for analytics and reporting.

Associate - Data and Analytics

Infosys

2021-10 - 2022-12 · 1 yr 3 mos

Richardson, Texas

• Developed an SQL schema mapping in Excel for a major pharmaceutical company to rename 400+ variables, enhancing clarity for Cloud Engineering stakeholders, including a product owner, while working cross-functionally with data and engineering teams. • Refactored variables in Python and SQL scripts for a 10TB database, improving code readability, maintainability, and consistency across teams. • Systematically applied naming conventions to ensure uniformity across the data pipeline while maintaining zero downtime and minimizing business disruptions.

Data Science Intern

Novo Nordisk

2020-6 - 2020-8 · 3 mos

Seattle, Washington

• Identified 12 obesity predictors and narrowed down to 2 by analyzing a dataset of 4000+ patient records using Python and Principal Component Analysis; Managed the project from end-to-end with minimal guidance. • Presented major obesity driver insights to an audience of 150+, including 4 heads of units and 6 data scientists, enabling data decisions for enabling data-driven decisions for targeted obesity interventions. • Defined project scope and ensured alignment with business objectives by collaborating with a research data scientist.