Leveraged HubSpot API for integration across marketing, sales, customer service, and content management, optimizing data flow and communication Developed a Python automation script to analyze campaign data, identifying areas requiring additional resources such as hours and signs, streamlining operational efficiency, and lowering campaign expenses by 10%Designed and implemented a recommendation model in Python for campaign optimization, providing insights on the specific signs and campaigns that yield the highest impactIntegrated machine learning and automation with data-driven decision-making processes to improve resource allocation and campaign performanceImplemented monitoring systems to track and analyze the performance of campaigns, adjusting strategies based on real-time data for continuous improvement which improved customer satisfaction by 5%

Created comprehensive and secure RESTful APIs, configuring specific settings for permissions, parsers, and renderers to integrate and manage data seamlessly Implemented intelligent cross-site user tracking mechanisms to gather valuable user dataEngineered, rigorously tested, and debugged dashboards to provide valuable insights to clients and customers

Improved the accuracy of the topic-building model by helping the company understand better the hot topics discussed on Twitter in Saudi Arabia.Created a topic-building model to identify and track hot topics on Twitter in Saudi ArabiaEmployed NLP principles such as BOG - vectors of word frequencies, Frequency of words, and TF-IDF vectors Applied Linear Discriminant Analysis (LDA) LSA model to create a supervised algorithm for more accurate resultsLeveraged the DNN to estimate tweets for Twitter users on specific hot topics in several geographic locationshttps://github.com/Ochie123/Citytopic-modeling

Demonstrated and conducted in-depth research, designed and implemented experiments, and validated findings about NLTK and spaCy in natural language processing and data science.Conducted a comprehensive analysis of the NLTK and spaCy NLP libraries to evaluate their respective capabilities in text analysis and processing.Executed the research plan, implementing a series of experiments and benchmarks to assess the two libraries' performance in tasks such as tokenization, POS tagging, and NERAnalyzed and validated the research findings, highlighting the strengths and weaknesses of each libraryhttps://www.researchgate.net/publication/375632138_COMPARISON_OF_NLTK_AND_SPACY_LANGUAGE_PROCESSING_LIBRARIES

Developed comprehensive RESTful APIs to integrate data, facilitating order fulfillment and real-time updates for a third-party dispatch serviceConducted end-to-end (E2E) testing using Selenium to validate user operations on a websiteDesigned and seamlessly integrated Web sockets powered by Django channels into the projectImplemented Redis-backed channels for deployment, enhancing system performance and scalability