Teran C.

Key Skills

Software

Appen

Top Subject Matter

Nlp Domain Expertise

Rlhf Domain Expertise

Stem Domain Expertise

Top Data Types

Text

Image

Document

Top Task Types

Classification

Red Teaming

Freelancer Overview

AI Data Quality Specialist. Brings 3+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Internal, Proprietary Tooling, and Appen. Education includes Bachelor of Science, Georgetown University (2021). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

AI Data Quality Specialist

Text

As an AI Data Quality Specialist at CrowdWorks AI, I evaluated large language model (LLM) outputs for quality and alignment with guidelines. The work involved crafting prompt-response pairs and refining annotation frameworks to facilitate responsible AI training. I contributed to enhanced annotation processes and curated high-quality datasets for multiple domains. • Evaluated over 500 LLM-generated responses per week for accuracy, coherence, and safety • Authored prompt-response pairs for RLHF datasets across STEM, law, medicine, and creative writing • Improved annotation agreement by collaborating on guidelines and mentoring junior annotators • Flagged edge cases and policy violations, contributing to AI safety datasets

2023 - Present

Personal Project – LLM Bias Detection Dataset

TextRed Teaming

I led a personal project to curate an LLM Bias Detection Dataset comprising adversarial prompts. This initiative targeted uncovering demographic and factual biases in open-source language models. The work resulted in a published analysis and direct engagement from AI safety research communities. • Assembled a 2,000-entry dataset of diverse adversarial prompts for bias testing • Investigated and documented instances of demographic and factual bias in LLM outputs • Shared results with the AI ethics community, sparking significant engagement • Enhanced open-source safety datasets through systematic adversarial data generation

2024 - 2024

NLP Data Annotator

AppenTextClassification

As an NLP Data Annotator at Appen, I carried out diverse labeling tasks for clients building NLP pipelines. Projects included text classification, entity extraction, and coreference resolution for multilingual and monolingual datasets. I supported quality initiatives and provided actionable recommendations for annotation improvements. • Performed text classification and named entity recognition (NER) on English and Spanish datasets • Maintained a high annotation quality score above 98% for 12 project cycles • Provided feedback leading to updated company-wide annotation style guides • Engaged in multilingual and multi-project annotation initiatives

2021 - 2022

Argument Quality Annotator Tool – Open Source Project

TextClassification

I developed an open-source Argument Quality Annotator Tool to facilitate annotation of argument strength and evidence quality in news articles. The annotation workflow was tailored for research labs and focused on streamlining classification tasks. The tool was successfully adopted in research environments and enabled rigorous argument analysis. • Created a Python GUI for argument strength and evidence quality labeling • Customized workflows for efficient annotation in research pipelines • Supported replication in multiple university research settings • Contributed to open-source tools for NLP and argument analysis

2021 - 2021

Research Assistant – Computational Linguistics

TextClassification

As a Research Assistant in Computational Linguistics at Georgetown University, I annotated corpora for discourse analysis and syntactic parsing. My responsibilities encompassed text data preparation and quality-focused annotation for academic research. Collaborative and automated approaches were adopted to streamline annotation tasks. • Annotated text corpora for discourse and syntax research projects • Built scripts to preprocess and clean raw text data for annotation • Co-authored a conference poster on automated argument mining using annotated data • Contributed to university research with data quality improvements

2019 - 2021

Education

Work History