Hanson C.

Key Skills

Software

Appen

Scale AI

Top Subject Matter

Conversational AI

Nlp Domain Expertise

Computer Vision

Top Data Types

Audio

Image

Text

Document

Top Task Types

Transcription

Bounding Box

Freelancer Overview

Senior Data Annotation Specialist. Core strengths include Appen, Rev.com, and Scale AI. Education includes Bachelor of Science, University of Arizona (2019). AI-training focus includes data types such as Audio and Image and labeling workflows including Transcription and Bounding Box.

Labeling Experience

Senior Data Annotation Specialist

AppenAudioTranscription

Oversaw large-scale audio transcription for conversational AI, consistently maintaining high accuracy across multilingual datasets. Performed Named Entity Recognition, coreference resolution, and intent labeling for natural language processing pipelines. Delivered computer vision image and video annotations including bounding box, polygon, and semantic segmentation for machine learning workflows. • Transcribed 10,000+ hours of multilingual audio for ASR training • Produced entity, intent, and coreference labels for enterprise chatbots • Conducted visual data annotation using bounding box and segmentation tools • Led annotation QA using inter-annotator agreement analysis

2022 - Present

Audio Transcription Specialist

AudioTranscription

Transcribed over 8,000 hours of audio and video content for diverse industries including legal, medical, academic, and media. Specialized in high-accuracy verbatim transcription and delivered time-stamped, speaker-identified, and caption-formatted data for machine learning accessibility compliance. Maintained quality above 99% and adapted to complex content typologies and client requirements. • Produced SRT/VTT captions for media accessibility • Handled podcast, interview, and focus group transcription • Managed deadlines for high-volume projects • Ensured compliance with detailed labeling policies

2020 - 2021

Data Labeling Analyst

Scale AIImageBounding Box

Labeled image and LiDAR data for autonomous vehicle perception, including 2D and 3D bounding boxes, lane, and road marking annotations. Annotated textual data for sentiment, topic classification, and content moderation in NLP pipelines. Maintained batch quality by reviewing annotations from a team of over 20 contractors and participating in iterative label taxonomy refinement. • Provided road marking and lane annotation for AV datasets • Labeled sentiment, topic, and moderation content in text • Engaged in ontology and taxonomy review sessions • Checked annotation quality for large-scale perception projects

2019 - 2020

Education