Machine Learning Data Science

Ayman IslamBerkeley, CA 310-***-**** **************@********.*** LinkedIn:

https://www.linkedin.com/in/ayman-islam-3a32291aa/ Education

University of California, Berkeley December 2025

Bachelor of Arts in Data Science

Relevant Coursework: Data Structures & Algorithms, Modern Statistical Prediction & Machine Learning, Principles & Techniques of Data Science, Data Inference & Decisions, and Human Contexts & Ethics of Data Skills

Programming Language & Tools: Python, SQL, Java, R, Ruby, Scheme, Git, Jupyter Notebook, Tableau, Excel, Apache Airflow, MongoDB, PostgreSQL, MySQL, TimescaleDB, Ruby on Rails Data Analytics and Machine Learning: Pandas, Numpy, Scikit-learn, Matplotlib, Seaborn, Transformers(Hugging Face), OpenCV, NLP, Regression, Classification, Clustering, Time-Series, Hypothesis Testing, Statistical Inference, Bayesian Methods, Simulation, EDA, Data Visualization, Predictive Modeling, Causal Inference Data Engineering & Software Development: ETL Pipelines, CI/CD, Agile Methodologies, Unit & Integration Testing, Modular Design, Cloud/Saas Deployment, Data Cleaning, Data Wrangling Work Experience

Software Consultant: WebAI Spring 2025

● Architected and implemented a pipeline to generate concise summaries of long-form videos (Python)

● Parallelized transcript chunk processing and frame inference to summarize a 40+-minute video in under five minutes using GPU acceleration (Python, CUDA)

● Integrated video/audio segmentation and transcription workflows (MoviePy, OpenAI Whisper) to produce accurate transcripts

● Applied NLP models to distill spoken content into key bullet points (Hugging Face Transformers)

● Employed frame-level object detection to identify scene changes and merge visual cues with text summaries (OpenCV, YOLOv8)

● Documented system design and maintained the end-to-end codebase in GitHub (Git) Projects

TimeSeriesDB Market Analysis(Personal Project)Summer 2025

● Designed a TimescaleDB hypertable schema to store historical multi-ticker OHLCV data from Yahoo Finance

● Developed Python ETL scripts to backfill historical market data and automate daily incremental loads

● Created continuous aggregate views with daily time buckets and configured compression policies

● Built interactive Tableau dashboards featuring moving averages, rolling volatility, and top-mover analyses

● Authored advanced SQL queries using window functions and CTEs to compute rolling metrics (e.g., volatility, inter-symbol correlations) for deeper market insights Quantitative Research Virtual Experience, JPMorgan Chase & Co. via Forage Spring 2025

● Analyzed commodity price data to identify market trends

● Developed Python scripts for data processing and financial modeling

● Applied quantitative methods to assess risk and forecast financial scenarios Data Science Virtual Experience Program, Boston Consulting Group (BCG) via Forage Spring 2025

● Analyzed client data to identify factors contributing to customer churn

● Developed predictive models to assess customer retention strategies

● Presented actionable insights to inform business decisions

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