Data Scientist

Personal summary

A 3X Kaggle expert, Data Scientist, and Artificial Intelligence Engineer, who aims at harnessing his analytical, statistical, logical, technical, and strategic acumen, while proactively working towards earning gainful experience in the industry. Placing a firm belief in the power of innovation and an unrelenting will to learn, for his overall growth as well as that of the organization. Currently, I am pursuing my master's in Applied Computing in the Artificial Intelligence stream at the University of Windsor. Expertise: Data Science, Machine Learning, Computer Vision, Data Analytics, Data Visualization, Time Series Analysis, Forecasting, and Technical Consulting Soft Skills: Problem-solving, Critical and logical thinking, Communication Skills, Fast Learner, Adaptable, Team Player, Curious, and Enthusiastic. • Programming - Python, R, C, SQL, LaTeX • Data Bases - MSSQL, MySQL, Impala, MongoDB • Library & Frameworks - Scikit-learn, Tensorflow, Keras, PyTorch, Transformers, YOLO, OpenCV, MediaPipe, dlib, Caffe, NLTK, SpaCy, ScanPy, Pandas, NumPy, SciPy, Scikit-learn, matplotlib, seaborn, plotly, PySpark, CNN, RNN, Flask, FastAPI, Streamlit, Docker, SQLite, Agile(Scrum), Linux, MLflow, hugging face • Tools - Git, Advanced MS-Excel, Talend ETL Tool, Jupyter NoteBook, RStudio, Anaconda, SSMS, Cloudera, MS-Suite, JIRA, Spyder, VS Code, Google Colab • Data Visualization Tools - Tableau, Power BI, Google Data Studio, MS-Excel • Natural Language Processing - NLTK, SpaCy • Web Development - HTML, CSS • Data Science Skills - Data Analysis, Data Mining, Data Cleaning, Statistical Analysis, Predictive Analysis, Time Series Forecasting, Statistics, Recommendations System, Machine Learning, Deep Learning (ml), Computer Vision, Artificial Intelligence (AI), Generative AI, Natural Language Processing (NLP), Large Language Models (LLM) • Cloud Deployment - Google App Engine, Google Cloud Platform (GCP), Microsoft Azure, Heroku • Application Lifecycle Methodologies - Agile and Waterfall • ML model deployment with Flask, Docker, and Heroku. • Knowledge of end-to-end Machine learning model development from data collection, to preprocessing, cleaning, modeling, hyperparameter tuning, evaluation, interpretation, and deployment.

Skills

Python5 Machine learning5 Data science5 Computer Vision3 Data analysis3 SQL3 Tableau3 Microsoft Power BI2