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Michelle Griffith

Data Scientist @BambooHR

Moab, UT, US
MOBILE NUMBERS
+17•••••••26

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WORK HISTORY

Apr 2024 — Present

Data Scientist @BambooHR

Salt Lake City, UT, US

Spearheaded the development, deployment, and monitoring of modular, scalable machine learning models to detect fraudulent HRIS software usage, resulting in the successful identification and cancellation of 21+ fraudulent accounts in just one month.Automated and optimized data pipelines by integrating Snowflake with Salesforce APIs, streamlining human review processes for enhanced operational efficiency.Leveraged Docker (ECR) and Kubernetes (EKS) on AWS to deploy ML models, ensuring robust scalability and reliability across platforms.Championed team best practices for machine learning model deployment, contributing to the foundational growth and scalability of the AI & Labs team.Delivered Propensity scores for expansion sales and winback opportunities, conducting detailed analyses of key features for each prediction. Insights, including feature values and percentiles, informed tailored customer messaging strategies to maximize engagement and conversion.

EDUCATION

N/A

Thinkful

Data Science Flex

N/A

Colorado School of Mines

Bachelor of Science (B.S.), Engineering Physics

N/A

Georgia Institute of Technology

Master of Science - MS, Computer Science

SKILLS

MathematicaSalesforce.comConstant ContactLatexTechnical WritingOpticsMicrosoft OfficeVacuum PumpsVacuum ChambersMachiningCnc MillLinuxInkscapeSolderingAnalog Circuit Design

ABOUT MICHELLE GRIFFITH

Ask me about my favorite books or what I\'m working on in my MS CS program right now.Or message me with your recommendations on books about: data, feminism, social and environmental commentary, practical applications of mathematics, history, anthropology, classic literature, or philosophy and human behavior.Okay now onto business.I am a machine learning engineer and full-stack data scientist who builds and ships end-to-end ML systems, from data pipelines and feature engineering through production deployment, monitoring, and interpretable outputs that prioritize real users.I currently build and maintain production ML systems in SaaS environments, including fraud detection and propensity modeling, and I am pursuing an M.S. in Computer Science with a Machine Learning specialization at Georgia Tech.I am motivated by building trustworthy, transparent technology that improves the human experience. In parallel with my technical work, I am an entrepreneur and community builder working across applied AI, creative product businesses, and community-based arts initiatives.Rest assured, I am in fact a real person, in case you had any doubts based on my totally normal super realistic profile picture.

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