Abraham Tedla

Data Scientist with 6+ years of enterprise data management, database engineering, and systems optimization experience, complemented by graduate-level training in machine learning, deep learning, and NLP. Proven track record building predictive models, designing statistical analyses, and delivering data-driven insights across banking, cloud, and corporate environments. Experienced in Python, R, SQL, and visualization tools including Tableau and Power BI. Passionate about applying AI and advanced analytics to solve complex business problems.

Education

Projects

TLigBind: Molecular Docking Web Platform: Developed full-stack drug discovery tool deployed on AWS Fargate with Streamlit, AutoDock Vina, RDKit, and EFS. Features user auth, job queuing, receptor/ligand prep, parallel docking, and community submissions. Manuscript in preparation.

Three-Class Sentiment Analysis in Movie Reviews: Authored research paper evaluating five deep learning architectures (LSTM, BiLSTM, CNN, GRU, BERT) for three-class sentiment classification on 50K IMDb reviews; achieved macro-F1 of 0.784 with BERT and conducted systematic ablation studies on architecture components, embedding strategies, and hyperparameters

Exploratory Text Analytics of Gothic & Sci-Fi Literature: Authored digital humanities research report analyzing 12 novels through a complete NLP pipeline: tokenization, TF-IDF, PCA, LDA topic modeling, and word2vec embeddings; identified cross-genre thematic patterns and cultural evolution in Gothic and Sci-Fi literary traditions

Humanitarian Image Classification - 2010 Haiti Earthquake: Developed computer vision model to identify displaced persons in post-earthquake satellite and ground imagery; applied convolutional neural networks and image preprocessing techniques to support humanitarian response efforts and damage assessment

Professional Experience

Developer & Co-Author May 2026 – Present

Trinh Laboratory, University of Virginia

Developed TLigBind, a full-stack molecular docking web platform for drug discovery research deployed on AWS Fargate
Architected CI/CD pipeline with GitHub Actions, ECR, and ECS with EFS-persistent storage
Implemented security hardening: path traversal protection, brute-force lockout, PDBQT validation, and non-root containers
Co-authoring manuscript for publication (August 2026)

IT Support Engineer November 2025 – Present

Amazon – Boston, MA

Providing high-quality on-site technical support for Amazon's corporate workforce, delivering seamless end-to-end IT services for laptops, servers, and corporate systems
Diagnosing, troubleshooting, and resolving specialized hardware and software issues across Windows, Mac, and Linux environments in a fast-paced, high-availability corporate setting

Systems Support Specialist June 2023 – October 2025

Computer Repair Specialists, LLC – Las Vegas, NV

Automated data reporting with Python and Bash scripts, reducing manual work by 40%
Configured Debian and Red Hat servers, ensuring secure and stable operations
Supported MySQL/MariaDB databases with automated backups and performance tuning

Systems Administrator January 2018 – June 2024

Commercial Bank of Ethiopia – Remote

Monitored system health metrics and evaluated log files to proactively identify performance bottlenecks, implementing preventive measures that reduced incidents by 30%
Oversaw Oracle Exadata migration, achieving major performance improvements
Designed KPI dashboards in SQL and Tableau enabling data-driven decision making

Technical Skills

Languages: Python, R, C, SQL, Shell Scripting, PowerShell

Machine Learning & AI: Predictive modeling, NLP, deep learning (CNNs, transformers/BERT), Bayesian methods, random forests, boosting, decision trees, SVMs, LDA, word2vec

Data & Visualization: Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch, Matplotlib, Seaborn, Tableau

Databases: Oracle, MySQL, MariaDB, MS SQL Server, MongoDB

Tools & Infrastructure: Git/GitHub, Docker, Hyper-V

Operating Systems: Windows, Debian/Red Hat Linux, IBM AIX

Professional Summary

Education

Projects

Professional Experience

Technical Skills