Fauzan Mohammed

I am a highly skilled data scientist with a strong technical background in statistical analysis, machine learning (ML), and deep learning (DL), including expertise in computer vision. I have a proven track record of working with large and complex datasets, using frameworks such as TensorFlow and PyTorch, to extract valuable insights and patterns. My proficiency extends to a wide range of algorithms and techniques, including regression, classification, clustering, and convolutional neural networks (CNNs) for computer vision tasks. I am well-versed in implementing these techniques using popular frameworks like Scikit-learn, Keras, and OpenCV. In addition, I possess hands-on experience in deploying ML models in production environments, utilizing frameworks such as Flask, Django, and Heroku. I am adept at optimizing and fine-tuning models for improved performance, leveraging techniques like transfer learning and ensemble methods. My expertise spans diverse domains such as finance, healthcare, and e-commerce, where I have successfully applied data science methodologies to solve complex problems. With my in-depth knowledge of frameworks and tools, coupled with a passion for innovation, I am equipped to contribute valuable insights and drive data-powered decision-making within any team or organization In summary, I bring a comprehensive skill set in data science, ML, and DL, with proficiency in frameworks like TensorFlow, PyTorch, scikit-learn, Keras, OpenCV, Flask, Django, and proficiency in Web Development. Furthermore, I am committed to continuous learning and growth in the rapidly evolving field of data science, staying updated with the latest advancements and techniques to ensure that my skills remain at the cutting edge of the industry.

Data Analyst at Qwaba, Accra, Ghana

• Utilized Python and SQL to analyze KPIs and customer data, resulting in a 50% increase in client base and 30% revenue growth.
• Developed machine learning models using scikit-learn for accurate forecasts and cost reduction.
• Applied regression and time series analysis to drive data-driven decision-making.

Junior ML Engineer at Omdena Thraive Project, Remote

• Designed and implemented NLP models using NLTK and scikit-learn for sentiment analysis and topic modeling.
• Conducted data cleaning, preprocessing, and feature engineering using pandas and NumPy.
• Employed data visualization techniques for exploratory data analysis.
• Developed robust and scalable Python code following software engineering principles and utilized Git for version control.

M.S. in Information Technology, Data Science & Analytics - Rensselaer Polytechnic Institute, Troy, NY

• Specialized coursework in Data Structures, Data Science, Software Development, Data Analytics, Database Management System, Information Security, Introduction to AI, Machine Learning, Business Issues, Computer Vision, Data Mining and Warehousing.
• Proficiency in programming languages such as Python, R, Lua, and MATLAB.
• Technical skills include Pandas, NumPy, PyTorch, Matplotlib, TensorFlow, Keras, Scikit-learn, OpenCV, MySQL, Tableau, Jupyter Notebook, RStudio, GCP, A/B testing, ETL, and data science pipeline.