Elma Fortunate Phiri
Data Scientist/ Data Analyst
Based in Bulawayo
About
I am a data science graduate passionate about solving complex problems through data-driven insights. I hold a BSc degree in Data Science from Adikavi Nannaya University, where I gained knowledge in the theoretical and practical aspects of data science, including machine learning, data mining, and data visualization. To complement my formal education, I actively pursue online courses on platforms like DataCamp and Coursera, while gaining hands-on experience through virtual internships and personal projects. My technical skills include proficiency in Python, Power BI, and SQL, and I am consistently working to improve my machine learning capabilities. I'm currently seeking internship opportunities where I can apply my knowledge, contribute to impactful data projects, and gain deeper knowledge
Skills
Projects
Experience
February 2025 - April 2025
Data Analyst Intern - DataVerse Africa, Nigeria
Led data-driven projects tackling key issues across Africa. Researched “Bridging the Data Gap Across Africa” by analyzing 100+ datasets across six sectors using Excel and Power BI to identify gaps and inform policy. Investigated seasonal income patterns for 70% of Uganda’s agriculture-based population, revealing a 68% necessity spending rate and 46.7% reliance on risky coping methods. Built ML models (83% accuracy) predicting financial stress, proposing solutions to cut asset sales by 30%. Developed hypertension risk models (84% accuracy, 58% recall) using lifestyle data, with dashboards highlighting demographic risk hotspots. Analyzed ₦1.9T in import data from 77,789 transactions to expose trade inefficiencies and high-tax outliers across 11,113 businesses.
December 2024- March 2025
ML and AI Internship - ULearn, India
Developed and deployed machine learning models using Python, utilizing libraries such as scikit-learn, TensorFlow, and Keras. Performed data preprocessing, feature engineering, and model evaluation on real-world datasets. Conducted exploratory data analysis (EDA) to uncover trends and inform model development. Developed a real-time human face detection system using deep learning techniques such as convolutional neural networks (CNNs) and computer vision libraries like OpenCV, Dlib, and Face Recognition. Applied data augmentation, parameter sharing, and tuning techniques to optimize model performance, and used tools like scikit-learn, XGBoost, and Matplotlib for model building and evaluation.
January 2025- February 2025
Data Science Intern - CodeAlpha, Remote, India
• Developed a car price prediction model using Python and machine learning algorithms to optimize pricing strategies. • Conducted Sales Analysis to identify key trends and patterns • Analyzed unemployment data in India pre- and post-COVID to provide insights for policy recommendations.
May 2024- July 2024
INTERNSHIP ON AI & ML USING PYTHON - ULearn, India
Developed and deployed machine learning models using Python, leveraging libraries such as scikit-learn, TensorFlow, and Keras for data preprocessing, model training, and evaluation. Conducted feature engineering, hyperparameter tuning, and performance optimization to improve model accuracy. Applied models to real-world datasets, delivering actionable insights and supporting data-driven decision-making.
June 2024 - July 2024
Data Science Intern- Prodigy InfoTech- India,Remote
The key projects I contributed to: Titanic Survival Prediction (Python): Built a predictive model to forecast passenger survival using techniques like Logistic Regression, and Random Forests. Utilized Pandas for data wrangling, and scikit-learn for model implementation and evaluation. Enhanced model performance through feature engineering and hyperparameter tuning. USA Road Accidents Analysis (Power BI): Created dynamic, interactive Power BI dashboards to analyze and visualize trends in road accidents across the USA. Identified high-risk regions, common accident causes, and seasonal trends Bank Marketing Campaign Analysis (Python): Analyzed customer data to predict the success of bank marketing campaigns using classification algorithms such as Logistic Regression
January 2024-February 2024
Data Analyst intern (Intern Career, Remote, India)
Project 1: YouTube Streamer Analysis. I conducted a well-detailed analysis of the dataset using Python to identify streaming trends. Identified top-performing content creators based on likes, subscribers, comments, and visits. Project 2: World Terrorism Analysis Using Power BI. In this project I analyzed the global terrorism trends using the global terrorism dataset. I identify the most targeted facilities by terrorist groups, the number of successful terrorist attacks, and the geographical distribution of terrorist attacks. I created an interactive dashboard to highlight key findings and insights from our dataset.
Education
August 2022- March 2025
Bachelor of Science in Data Science - Adikavi Nannaya University
This is a comprehensive 3-year program. This program equips me with a solid foundation in data analysis, machine learning, and data visualization.
June 2024 - May 2025
Applied Data Science Lab- World Quant University
In this program, I will work on 8 different projects, which will allow me to harness and enhance my Python and data science skills. These projects are designed to provide hands-on experience and practical knowledge, enabling me to apply theoretical concepts in real-world scenarios. Through these projects, I aim to deepen my understanding of data analysis, machine learning, data visualization, and other essential data science techniques.
April 2024 - September 2024
Associate Data Scientist in Python - DataCamp
This career track covers topics from data manipulation to machine learning, providing me with the skills needed to succeed as a data scientist