John F.

Key Skills

Software

AWS SageMaker

Top Subject Matter

Customer analytics

Personalization Domain Expertise

sentiment analysis

Top Data Types

Text

Document

Top Task Types

Fine-tuning

Segmentation

Classification

Freelancer Overview

Senior Data Scientist in Contract Review, Compliance, and Legal Research. Brings 9+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include MLflow, Azure ML, and AWS SageMaker. Education includes Doctor of Philosophy, University of Virginia (2018) and Bachelor’s Degree, Oregon State University (2012). AI-training focus includes data types such as Text, Computer Code, and Programming and labeling workflows including Fine-tuning, Segmentation, and Sentiment Analysis.

Labeling Experience

Senior Data Scientist – AstroSirens (Jan 2022 – Present)

TextFine-tuningSegmentation

Built and deployed deep learning models using PyTorch and TensorFlow for customer segmentation and personalized recommendations based on user interaction signals. Developed real-time sentiment analysis using Hugging Face Transformers and exposed an LLM-powered responder API to production. Led iterative model development with experiment tracking and model versioning to improve downstream metrics over time. • Deep learning model development and deployment for personalization and segmentation. • Sentiment analysis dashboard and NLP-based extraction from customer feedback. • Real-time LLM responder API orchestration with containerization and scaling. • A/B testing and Bayesian experimentation to evaluate model/feature impact.

2022 - Present

Machine Learning Engineer – Pinterest (Nov 2019 – Jun 2021)

Fine-tuning

Developed and deployed predictive maintenance, anomaly detection, recommendation, NLP, and time-series forecasting models. Implemented real-time personalization APIs and designed classification models in collaboration with fraud detection teams. Used A/B testing and statistical/causal inference techniques to guide model- and feature-driven product decisions. • Training models for IoT predictive maintenance and streaming anomaly detection. • Recommendation model development using collaborative filtering and matrix factorization. • NLP pipelines for entity and relationship extraction from unstructured text. • Forecasting and classification model deployment with experiment-driven evaluation.

2019 - 2021

Data Science Intern – Census (Sep 2018 – Sep 2019)

AWS SageMakerText

Supported building ETL pipelines and automating data workflows using Python and SQL. Assisted senior data scientists in analyzing user metrics and running A/B tests to validate product or modeling ideas. Helped build dashboard visualizations and ensure accuracy in key business reports. • ETL automation enabling downstream analytics for model/experiment evaluation. • Support for A/B test execution and analysis of user metrics. • Dashboard and reporting support for experiment results interpretation. • Data quality checks to maintain accuracy of analysis outputs.

2018 - 2019

Education

Work History