Position: Data Scientist
Category: Data Science
English level: fluent
Years of experience: 4


As an experienced Machine Learning Scientist with 10+ years in the IT sector and higher education, I excel in research and high-level development projects using ML models. Skilled in dimension reduction, feature extraction, and data manipulation with Python. Developed ML models for real-life data (parametric and non-parametric) like K-means clustering and XGBoost. Proficient in Deep Learning and NLP with transformer models for complex problem-solving. Experienced in setting up end-to-end pipelines on Docker and AWS. Strong programming skills in low-level/high-level languages and scripting. Thrive in diverse international teams, leading agile (scrum) and managing large groups.

Projects:
- NLP for Amharic: Improved accuracy from 62% to 92% using Logistic Regression, SVM, and XGBoost.
- Clone detection on coding data: Led NLP project with CodeBERT, UniXcoder, and Doc2Vec for accurate results.
- Price prediction on trading data: Used Linear, Ridge, Lasso Regression, AdaBoost, XGBoost for trend prediction. Utilized Pandas, Numpy, Matplotlib, Seaborn.
- EDA on heart stroke data: Analyzed multivariate biological data using KNN, Logistic Regression, Pandas, Numpy, Seaborn, Yellowbrick.
- Microarray gene-expression analysis: Employed PCA, SVD for dimensionality reduction. Used feature selection, ANN, KNN, DT, RF, SVM. Improved cancer classification.

Completed 20+ ML, Deep Learning, NLP projects.

Looking to enhance skills in Data Engineering and Data Science Engineering. Goal is to design efficient data pipelines, manage large-scale infrastructure, and optimize data-driven solutions.