Karolline Stenning

Key Skills

Software

Appen

AWS SageMaker

Top Subject Matter

Digital Health

Medicine Domain Expertise

AI Medical Content

Top Data Types

Text

Document

Top Task Types

Classification

Segmentation

Text Generation

RLHF

Text Summarization

Data Collection

Freelancer Overview

As a medical doctor with over 10 years of clinical, research, and digital health experience, my core value in AI training lies in domain expertise rather than volume annotation work. My background spans primary care, surgical medicine, Phase III clinical trials, and healthtech entrepreneurship, giving me the clinical depth to evaluate AI-generated medical outputs for accuracy, safety, and appropriate reasoning. While my AI training experience is in its early stages, the judgment skills I apply daily as Chief Medical Officer of a healthtech startup, reviewing evidence-based content, assessing clinical accuracy, and identifying misleading health information, are directly transferable to RLHF medical evaluation and hallucination auditing tasks. I understand not just whether a medical statement is technically correct, but whether it is appropriate, safe, and well-reasoned for its intended context, which is the nuanced judgment that separates a medical expert reviewer from a general annotator. My academic background further strengthens this profile: I hold an MSc in Bioentrepreneurship from Karolinska Institutet with a thesis on digital health implementation, and I completed Harvard University's clinical research programme, which trained me in the critical appraisal of medical evidence, a skill directly applicable to assessing the quality and reliability of AI-generated clinical content. I am fully bilingual in English and Spanish, enabling expert-level medical review across both languages. AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

Education

Work History