Kristen M.

Key Skills

Software

Other

Mercor

Don't disclose

Top Subject Matter

Clinical Genetics/Genomics

Cardiology - Cardiomyopathy and Heart Failture

Clinical Data Manager integrating AI-assisted LLM support

Top Data Types

Document

Image

Audio

Top Task Types

Diagnosis

Text Generation

Question Answering

Evaluation/Rating

Data Collection

RLHF

Bounding Box

Object Detection

Text Summarization

Transcription

Prompt + Response Writing (SFT)

Classification

Freelancer Overview

Clinical Data Manager — Cardiac Genetics & Inherited Cardiomyopathy Research. Brings 10+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Master of Science, Regis University (2021) and Bachelor of Science, University of Texas at Austin (2015). AI-training focus includes data types such as Medical and DICOM and labeling workflows including Diagnosis.

Labeling Experience

AI Data Annotation & Prompt Evaluation (Confidential Client)

TextRLHF

Conducted structured evaluation and grading of AI-generated outputs across complex prompt scenarios, focusing on reasoning quality, consistency, and adherence to guidelines. Applied detailed annotation frameworks to identify edge cases, ambiguity, and failure modes, while providing written rationale to support dataset quality and model evaluation workflows. Contributed to improving data reliability for downstream model training and alignment.

2026 - Present

Clinical Text Annotation & Validation for Antidepressant Data Modeling

TextData Collection

Expert validation of 100 antidepressant patient reviews (1,600+ labels), with structured categorization and rationale to support model training, evaluation, and consistency.

2026 - Present

Clinical Data Manager — Cardiac Genetics & Inherited Cardiomyopathy Research

Diagnosis

Developed and implemented AI-assisted parsing tools for multimodal cardiac imaging and clinical data using Python and LLM-directed workflows. Labeled and curated echocardiography, cardiac MRI, ECG, and telemetry datasets for machine learning applications in cardiomyopathy research. Oversaw DICOM deidentification and data governance for over 33,000 patient datasets, enhancing analytic power and standardization. • Led data acquisition and curation from diverse imaging modalities. • Directed labeling activities for clinical diagnosis classification. • Applied domain-expert logic to AI tool design and data preprocessing. • Managed integration of clinical, genetic, and imaging datasets for research utility.

2023 - Present

Education

Work History