Farah Kandil

• Conducted NIH-funded preclinical research analyzing pain-related behavioral outcomes and analgesic efficacy using animal models.
• Designed blinded experimental protocols and performed statistical analysis to compare treatment effects across conditions.
• Contributed analytical findings to a peer-reviewed publication (Frontiers in Pain Research, PMID: 37139343).

• Deliver individualized and small-group mathematics instruction, diagnosing learning gaps using data-informed feedback.
• Strengthen statistical analysis, quantitative reasoning, and multi-step problem-solving, translating complex concepts into clear analytical frameworks.

• Completed rigorous pre-clerk curriculum while maintaining a strong academic standing.
• Assessed patient needs through detailed evaluations and working with multi-disciplinary teams in various clinical environments.
• Contributed to advancements in medical knowledge - Perception of Osteopathic Medicine in a Rural Clinic in Peru (Survey Study) and The Effect of Energy Drinks on Colorectal Cancer Risks (Literature Review)

• Authored UX-driven, evidence-based medical educational content, translating complex clinical information into accessible formats and increasing user engagement by 50%+.

• Supported the launch of a new OB/GYN clinic by assisting with inpatient procedures, medical scribing, patient education, triage, and care coordination to enhance clinical efficiency and patient outcomes.

• Supported patient care delivery by documenting clinical encounters, orders, and results in the EHR and streamlined clinical workflows while facilitating provider communication.

Delivery Delay Analysis | Python, SQL, DuckDB, Pandas, Matplotlib | GitHub

• Built an end-to-end analytics pipeline on millions of NYC taxi trip records, transforming raw Parquet data into a validated, analysis-ready dataset using DuckDB and SQL.
• Engineered a delivery-time metric (minutes per trip) and produced hour-level aggregations to model temporal performance trends.
• Uncovered peak afternoon congestion associated with longer delivery durations through exploratory analysis and visualization, generating actionable insights for last-mile logistics optimization.

UX Friction Analysis | Power BI, Excel, Microsoft Clarity | GitHub

• Conducted behavioral analytics on 6,050 user sessions to quantify UX friction using Microsoft Clarity’s rage-click framework.
• Modeled severity (rage-click rate) and impact (total rage clicks) and visualized results in Power BI to support prioritization.
• Identified Checkout as the highest-friction page (20% rage-click rate), with Signup and Pricing as major contributors, enabling data-driven UX improvement decisions.

Bioinformatics Capstone Project | Python, MEGA X, MUSCLE, NCBI Datasets

• Performed Python-based sequence analysis and comparative genomics to study biological variation across viral datasets.
• Analyzed SARS-CoV-2 spike protein mutations across temporal and geographic samples to evaluate implications for long-term vaccine effectiveness.
• Discovered recurring mutation patterns and potential vaccine-driven selective pressures, supporting the need for regularly updated strain-specific vaccines.