Scott Nelson

N Star Holdings, Remote - Independent Technical Consultant

AUGUST 2024 - JANUARY 2026

• Served as the sole engineer and technical lead, a one-person team with full ownership of the technology, for a debt-collection business managing a $480K charged-off loan portfolio of roughly 370 debtors, working directly with a non-technical business owner through a legally complex Texas-to-California ownership transfer.
• Cleaned, consolidated, and standardized debtor records from 19 separate sources into a single, analysis-ready dataset, including a normalized data dictionary and code key.
• Designed and built prototype versions of a debtor self-service web portal using several full-stack approaches, including Firebase (Firestore and Cloud Functions), Supabase with a Postgres database on Vercel, and a Python Flask API, and used AI-assisted development tools to iterate quickly on design and usability.
• Built the core functionality: secure debtor onboarding and login with Firebase Authentication, SMS two-factor authentication and one-time passwords (OTP), server-side identity verification, account dashboards, and a PayPal checkout flow for online payments.
• Managed legally compliant debtor outreach across multiple channels, including required mailed legal notices, phone calls, and a prototype automated voice (IVR) system, to reach a difficult and often uncooperative population.

Meta, Remote - Linguistic Data Analyst

AUGUST 2023 - AUGUST 2024

• Collaborated with cross-functional teams (Engineering, Subject Experts, Product, Policy, and Research) to fine-tune LLM training datasets, ensuring safety and bias alignment in Meta AI’s Llama 2 & Llama 3 projects before deployment.
• Designed and executed 20,000+ adversarial prompts across dozens of harm categories and multiple model versions to stress-test model safety and surface weaknesses in language generation.
• Contributed to a 65% average reduction in policy violations across categories, with the largest gains in critical-hazard categories.
• Researched state-of-the-art techniques for LLM development, red-teaming, prompt optimization, and NLP evaluation metrics, and developed cross-cutting metrics and standards for model training.
• Communicated linguistic insights clearly to technical and non-technical stakeholders while accounting for computational constraints.

Loyola Marymount University, Los Angeles - Research Assistant

NOVEMBER 2021 - SEPTEMBER 2023

• Transformed raw EEG time-series into power spectral density (PSD) analyses supporting the neural efficiency hypothesis.
• Designed and crowdsourced a 290-article, ~2,200-annotation subjective-news-bias corpus (CNN/FOX/BBC), tagging each judgment with the reader’s political leaning and demographics to operationalize bias as reader-dependent.
• Built an ensemble pipeline (Longformer long-context transformer + decision tree) to predict readers’ subjective perceptions of article bias.
• Re-engineered an abandoned modeling pipeline into a leakage-free, CPU-only reproduction (<10s), catching a data-leakage bug affecting ~97% of validation and showing reader demographics outpredict article text (AUC 0.62 vs 0.53).

Tenant’s Law Firm, Los Angeles - Internship

MAY 2022 - DECEMBER 2022

• Automated data-intelligence reporting by integrating APIs and JSON data pipelines with the Customer Relationship Management (CRM) system, using a scheduled workflow automation tool (n8n) to prioritize workload for attorneys.
• Integrated a document drafting software to cut routine legal drafting time by 80% via digitization and automation.
• Ordered public records requests from the Los Angeles Metro area’s multiple municipal bodies; client/customer service.

San Jose State University, San Jose, CA - Master of Science in Applied Data Intelligence

JAN 2026 - (present)

Intended Grad Coursework: Mathematics for Data Intelligence • Data Visualization • Database Technologies • Deep Learning • Machine Learning • Data Engineering & Pipeline Development • Data Science • Optimization

Loyola Marymount University, Los Angeles, CA - Bachelor of Arts in Psychology

AUGUST 2019 - MAY 2023

Minors: Computer Science; Statistics & Data Science

Undergrad Coursework: Cognitive Neuroscience • Behavioral Neuroscience • Artificial Intelligence • Programming Abstractions • Data Structures • Research Methods • Multivariate Statistics • Applied Linear Algebra • Probability & Statistics

Grad-level Coursework: Data Science for Machine Learning • Cognitive Systems Design • Natural Language Processing • Agile Project Management