Work History

Delivered a comprehensive course curriculum for Data Analytics, covering topics such as data cleaning, exploratory data analysis, statistical modeling, and data visualization.

Conduct study halls, workshops, and group discussions to effectively communicate complex analytical concepts and methodologies to students with diverse backgrounds and learning styles.

Provide personalized guidance and support to students through office hours, online forums, and one-on-one consultations, helping them overcome challenges and achieve learning objectives.

Evaluate student performance through assignments, quizzes, and projects, providing constructive feedback and guidance for improvement.

Stay abreast of industry trends, best practices, and emerging technologies in data analytics, incorporating relevant updates and advancements into course content and teaching methodologies.

Collaborate with other instructors and educational staff to continuously enhance the quality and effectiveness of the Data Analytics program, ensuring alignment with industry standards and student needs.

Provide expert consulting services to clients in various industries, offering strategic guidance and technical expertise in machine learning, data science, and artificial intelligence.

Collaborate with clients to understand their business objectives, challenges, and data-related needs, developing tailored solutions and recommendations to address specific requirements.

Conduct comprehensive data analyses, including data cleaning, preprocessing, feature engineering, and predictive modeling, using advanced statistical and machine learning techniques.

Design and implement end-to-end machine learning pipelines, from data collection and preprocessing to model training, evaluation, and deployment, leveraging tools such as TensorFlow, Scikit-Learn, and PyTorch.

Perform in-depth exploratory data analysis (EDA) and data visualization to uncover insights, patterns, and trends in large and complex datasets, facilitating data-driven decision-making and business strategy.

Provide guidance on data infrastructure, architecture, and best practices, including data storage, retrieval, processing, and governance, to ensure scalability, reliability, and security of data assets.

Deliver clear and actionable insights, findings, and recommendations to clients through presentations, reports, and visualizations, tailored to diverse stakeholders, including executives, managers, and technical teams.

Offer expertise in areas such as natural language processing (NLP), computer vision, time series analysis, and reinforcement learning, depending on client needs and project requirements.

Stay updated on the latest advancements, trends, and best practices in machine learning, data science, and related fields, continuously enhancing skills and knowledge through self-study, training, and professional development opportunities.

Engineered a set of tools to periodically extract, clean, and process data from multiple sources.

Built an API for the Brownsville ETL tool, providing future developers a rapid and simple solution to retrieve the data from the data store.

Accelerated the residence repair process for members of the community of Brownsville in Brooklyn, NY.

Designed, built, and deployed the backend and frontend to host research articles using GoLang. The backend was created using GoLang, a language known for its industry leading performance, whereas the frontend was built using a wide array of state-of-the-art UI libraries for a pleasant user experience, further enhancing user engagement and average session duration.

Developed an editor panel which provides tools for creating blog posts and research publications.