About

Data Scientist & Machine Learning Engineer

Data Intern @ NVIDIA | M.S. in Data Science @ ASU | Data @ Alibaba

  • Pronouns: he/him/his
  • City: San Jose, California
  • Email: taha.mahmood.73@gmail.com
  • Website: www.tahamahmood.com

Passionate about unraveling insights from data through data analytics and machine learning algorithms, with a keen focus on Product Insights and Product Data. Excited to connect with fellow enthusiasts and collaborate on data-driven innovations in these cutting-edge domains. Let's shape the future together! 📊🤖👁️🔍

Interests

Machine Learning

Computer Vision

Natural Language Processing

Product Data Analysis

Visualization

Data Pipelines

Deep Learning

Reinforcement Learning

Education

Arizona State University, Tempe, AZ

Master of Data Science, Analytics and Engineering

2023 - 2025

  • EEE 549: Statistical Machine Learning
  • DSE 598: Statistics for Data Analysts
  • IEE 620: Optimization I
  • CSE 572: Data Mining

Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Topi, KPK

Bachelor of Science in Mechanical Engineering

2017 - 2021

  • ME 452: Robotics
  • ME 464: System Dynamics and Control
  • MS 492: Operations Management

Certifications

NVIDIA

Accelerating End-to-End Data Science Workflows

Issued Jun 2024

Explored on how to perform multiple analysis tasks on large datasets using RAPIDS, a collection of data science libraries that allows end-to-end GPU acceleration for data science workflows.

IBM

Data Science Professional Certificate

Issued Dec 2023

  • Mastered the most up-to-date practical skills and knowledge that data scientists use in their daily roles.
  • Learned the tools, languages, and libraries used by professional data scientists, including Python and SQL.
  • Imported and cleaned datasets, analyzed and visualized data, and built machine learning models and pipelines.
  • Applied my new skills to real-world projects and built a portfolio of data projects that showcase my proficiency to employers.

Google

Advanced Data Analytics

Issued May 2023

  • Explored the roles of data professionals within an organization.
  • Created data visualizations and applied statistical methods to investigate data.
  • Built regression and machine learning models to analyze and interpret data.
  • Communicated insights from data analysis to stakeholders.
  • Stanford University

    Machine Learning

    Issued Jun 2020

    • Built ML models with NumPy & scikit-learn, and built & trained supervised models for prediction & binary classification tasks (linear, logistic regression).
    • Built & trained a neural network with TensorFlow to perform multi-class classification, and built & used decision trees & tree ensemble methods.
    • Applied best practices for ML development & used unsupervised learning techniques for clustering & anomaly detection.
    • Built recommender systems with a collaborative filtering approach & a content-based deep learning method, and built a deep reinforcement learning model.

    Experience

    NVIDIA Corporation, Santa Clara, CA

    Data Service Intern

    May 2024 - Aug 2024

    • Conducted comprehensive analysis of Engineering Change Orders (ECOs) using ensemble methods and natural language processing (NLP) to identify and resolve root causes of business rule conflicts, achieving a 12% reduction in ECO lead time
    • Utilized a combination of outlier detection, consistency checks, and machine learning-based anomaly detection to identify and correct erroneous attribute values in electric and silicon parts inventories, reducing the error rate from 3.4% to 0.2%
    • Collaborated with engineers to design an AI NeMO Platform, leveraging textual analysis and computer vision techniques to accurately extract key attribute values from Electronics Parts Datasheets with 92% accuracy

    Alibaba Group (Daraz), Karachi, Pakistan

    Regional Data Product Specialist

    Jan 2023 - Aug 2023

    • Executed 7 Product A/B Testing strategies on the Buyer App leveraging statistical inference and hypothesis testing (t-tests, Chi-squared), resulting in a 25% reduction in bounce rate and an average user session increase from 1.35 mins to 1.68 mins
    • Spearheaded a monthly product presentation for the Live Commerce and Checkout interface, conducting competitive benchmarking and quantitative analysis to shape the product strategy and adjust the product roadmap for the upcoming sprint
    • Engineered a robust product sentiment analysis solution, leveraging BERT-NLP techniques to extract insights from customer reviews with 86% accuracy, thereby improving the strategic product curation process and addressing commercial needs
    • Refined a product recommender system with a team of 5 engineers, revolutionizing application user experience through personalized product recommendations, increasing Product Click-Through rate by 12%
    • Led the development of Badge Project, a data-driven initiative to expand visibility for subsidized items through enhanced assortment display, boosting weekly Gross Merchandise Value growth by $0.95 million across all five ventures
    • Performed comprehensive quality control (QC) checks on Flash Sale Datasets Pipelines, ensuring 100% data integrity

    Alibaba Group (Daraz), Karachi, Pakistan

    Management Trainee

    Jul 2021 - Dec 2022

    • Refurbished the chatbot system by replacing static answers with AI-led adaptive answers by refining the Recurrent Neural Network (RNN), increasing the Chatbot Resolution Rate from 68% to 79%
    • Integrated the profitability pipelines in the MaxCompute databases, and leveraged PowerBI and SQL to develop three customizable real-time profitability dashboards (NPM, GPM, and OPM) with the cost breakdown
    • Pioneered Live Commerce sequencing algorithm via IBCF-Feature Engineering to personalize stream ordering, resulting in a significant increase from 105,000 to 126,000 Stream Daily Active Users (DAU)
    • Employed advanced time series forecasting techniques (Logistic Regressions, Random Forest, XGBoost) to predict Live Commerce order surges, facilitating enhanced decision-making in demand planning and inventory management
    • Collaborated with business leadership and cross-functional stakeholders to establish the logic for 25 Live Commerce KPIs, subsequently developed a dashboard using SQL and Power BI to monitor and visualize the metrics effectively

    Skills

    Check My Skills

    Projects

    Chess AI: Empowered by Deep Q-Learning

    Chess AI: Empowered by Deep Q-Learning

    Reinforcement Learning

    Disaster Risk Monitoring Using Satellite Imagery

    Disaster Risk Monitoring Using Satellite Imagery

    Computer Vision

    Traffic Intelligence: Enhancing Urban Mobility

    Traffic Intelligence: Enhancing Urban Mobility

    Deep Learning

    SpaceX Falcon 9 Site Landing Prediction

    SpaceX Falcon 9 Landing Prediction

    Machine Learning

    AI Mathematical Olympiad: Elevating Math Reasoning

    AI Mathematical Olympiad: Elevating Math Reasoning

    LLMs

    Skin Cancer Detection with 3D-TBP Processing

    Skin Cancer Detection with 3D-TBP Processing

    Computer Vision

    Haptic robotic device for telesurgery

    Haptic robotic device for telesurgery

    Computer Vision, Reinforcement Learning

    Contact

    Contact Me

    Email Me

    contact@example.com

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