Fares H.

Key Skills

Software

Other

Don't disclose

Top Subject Matter

Pharmacovigilance (PV) and drug safety concepts

Pharmacovigilance (PV)

Pharmaceutical industry training (documentation and workflows)

Top Data Types

Text

Top Task Types

Classification

Data Collection

Text Summarization

Freelancer Overview

Drug Tour – EDA (Online) Training. Brings 4+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other and Don't disclose. Education includes Doctor of Pharmacy, Arab Academy for Science and Technology (2025). AI-training focus includes data types such as Text, Medical, and DICOM and labeling workflows including Classification, Data Collection, and Text Summarization.

Labeling Experience

Ai development

TextText Generation

I’ve spent the last 4 years working deeply in AI training and data annotation, mostly on top platforms like DataAnnotation.tech and Outlier. Over this time, I’ve done everything from evaluating model responses and writing justifications to red-teaming and prompt engineering. I genuinely enjoy making models smarter and more accurate. Because of my background, I also have a sharp eye for factual accuracy and love working on complex tasks that require real human judgment, always keeping my quality scores at the top

2022 - Present

Graduation Project – AAST Abu Qir Campus

OtherTextText Summarization

Completed a graduation project at AAST Abu Qir Campus that consolidated clinical/pharmaceutical knowledge into a structured academic output. Graduation projects typically involve producing written analyses that can be translated into text-labeling-style tasks such as summarization and structured reporting. The experience supports the ability to produce consistent, well-structured textual content. • Produced structured documentation as part of the graduation deliverable • Developed analysis and reporting skills suitable for text labeling workflows • Practiced organizing information into coherent outputs • Strengthened ability to summarize and present key findings

2025 - 2025

Hospital Pharmacy Training

Don't discloseClassification

Completed Hospital Pharmacy training, developing stronger familiarity with clinical documentation and medication-related workflows. The training required interpreting patient and medication context in order to support safe and accurate pharmacy actions. These skills are relevant to preparing well-structured clinical information for potential labeling tasks. • Interpreted medication and patient context during hospital pharmacy workflows • Reinforced safe handling principles aligned with structured clinical data use • Strengthened ability to support accurate categorization of clinical details • Improved documentation awareness for consistent downstream usage

2025 - 2025

General Clinical Pharmacy – Students University Hospitals

Don't discloseClassification

Completed General Clinical Pharmacy training at a university hospital setting, reinforcing clinical decision support concepts. While not explicitly an AI labeling role, the course involved working with patient-related clinical information that can translate into labeled clinical datasets. The experience supports learning how to interpret and categorize clinical details accurately. • Worked with clinical pharmacy processes and patient-care information • Reviewed therapeutic context to support consistent categorization • Strengthened understanding of clinical guidelines used to structure decisions • Built experience interpreting clinical information for downstream use

2025 - 2025

Industry Training

OtherTextData Collection

Completed industry training that supported clinical/pharmaceutical workflow understanding and documentation habits. The training emphasized observing real-world processes that generate structured information for downstream analysis. Such exposure helps develop the discipline needed for accurate data collection and labeling. • Observed how pharmaceutical information is recorded and organized • Learned practical documentation and reporting routines • Gained context for structured data generation from clinical activities • Built familiarity with quality expectations in data handling

2025 - 2025

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Education

Work History