Highly motivated data scientist with expertise in handling large datasets, statistical modeling, and machine learning. Proficient in predictive modeling, data visualization, and hypothesis testing to solve complex business problems. Experienced in data mining, database management, and deep learning. Adept at collaborating with cross-functional teams to deliver actionable insights and improve operational efficiency.
Conducted data processing, transformation, and management of large datasets using SQL and relational databases.
• Developed and maintained datasets to ensure consistency and accuracy, supporting decision-making across departments.
• Analyzed structured and unstructured data, delivering insights to optimize product development and marketing strategies.
• Designed and executed query wizards to compare and validate data tables for actionable insights.
• Partnered with cross-functional teams to define data requirements, enhancing data collection and reporting processes.
• Presented findings and recommendations to stakeholders, driving improvements in efficiency and alignment.
Conducted quality control checks and ensured compliance with Good Manufacturing Practices (GMP).
• Documented and reported quality-related incidents, ensuring adherence to safety and regulatory standards.
• Verified equipment cleaning and readiness to maintain high production quality.
Programming Languages: Python (Pandas, NumPy, Scikit-Learn, TensorFlow, Keras), R (ggplot), SQL (PostgreSQL, MySQL)
Data Science & Machine Learning: Regression (Linear, Logistic), Classification (SVM, Decision Trees, Random Forests), Clustering (K-Means, Hierarchical), Neural Networks, Deep Learning, Time Series Analysis
Data Analysis & Visualization: Power BI, Tableau, ggplot, Matplotlib, Seaborn, Interactive Dashboards
Database Management: Advanced SQL, Data Wrangling, Data Cleaning, Relational Database Design
Tools: Jupyter Notebooks, GitHub, Visual Studio Code, Smartsheet, Microsoft Office Suite (Excel, PowerPoint)
• CUSP Leadership Scholarship Program (2017 – 2021)
• Undergraduate Creativity Activity Research Experience (UCARE): Conducted research projects integrating data science methods.
• Peer Mentorship Program: Provided guidance to students, enhancing communication and leadership skills.
• Civic Engagement Certificate: Demonstrated commitment to community leadership and development.
• Predictive Modeling: Built machine learning models to forecast trends, including time series analysis and regression models.
• Data Analysis & Visualization: Developed interactive dashboards using Power BI and Tableau to communicate business insights.
• Deep Learning: Designed neural networks for image classification and sentiment analysis using TensorFlow and Keras.