Applied Data Analytics Graduate

Technical Skills: Python, R, SQL, Bash Scripting, AWS, GCP, Apache Spark, Apache Kafka, Power BI, Linux Programming

Education

M.S, Applied Data Analytics Boston University (Jan 2024)
B.S (Hons.), Computer Science Heriot-Watt University (May 2022)

Work Experience

Graduate Data Science Research Assistant (Dec 2022 - Present)
Boston University Henry M. Goldman School of Dental Medicine

Examined 40,000+ American’s tweets related to Vaccine and fluoride, to identify trends in beliefs.
Reduced manual assigning of sentiments on tweets by 40%; created a ML pipeline to perform Preprocessing, fine-tuning a transformer model to automatically assign sentiments.
Fine-Tuned an existing Transformer model to predict the sentiment of more than 40,000 tweets with an accuracy of 85%.
Developed correlation matrices and Bar plots to assess the trends over 3 time periods: Pre Pandemic, During Pandemic and post pandemic.
Skills: Python, Machine Learning, NLP, Predictive Modelling, Research Skills

Information Technology Help Desk Technician (Sept 2022 - Present)
Boston University Metropolitan College

Resolved 200+ tickets within a span of 1 year with over 90% client satisfaction rate.
Troubleshooted hardware and software issues such as Power BI, VMWare and Citrix Virtual Labs via ServiceNow ticketing system, phone calls and Bomgar remote desktop assistant.
Trained a team of 4 new hirees to assist clients with various troubleshooting tasks and handling clients face-to-face.
Skills: Team leading, Attention to detail, Customer-facing role, Management

Data Science Intern (Jun 2022 - Aug 2022)
Apparel Group

Optimized the inventory for the Charles & Keith brand by developing a sales predictive algorithm; Reduced unused inventory by an average of 15% per store.
Analyzed diverse data factors, such as customer demographics, store locations, seasonal trends, store sizes, and fashion cycles, to enhance the algorithm’s performance.
Deployed a Sales Predictor Model, with an accuracy of 75% at the time of deployment, providing valuable insights and optimization solutions for the brand.
Skills: Time Series Forecasting, Qualitative Analysis, Natural Language Processing (NLP), MicroStrategy, Microsoft Excel, PowerBi

Undergraduate Teaching Assistant (Sep 2021 - Jun 2022)
Heriot-Watt University

Provided teaching and support to students in introductory computer science courses, including Java, Python and R.
Graded student assignments and exams, and provided feedback to help students improve their learning.
Led weekly discussion sections and helped students understand complex concepts and solve problems.
Skills: Management, Research Skills, Git, Problem Solving, Python

Data Consultant (Nov 2020 - May 2022)
COGOS Technologies

Analyzed data and created a platform for integrating operations post-acquisition at Cogos.
Led machine learning projects for route and capacity optimization after the acquisition.
Demonstrated expertise in data-driven decision-making and machine learning.
Created a data warehouse and platform pre-acquisition.
Skills: Project Management, MS Excel, GitHub, Open Source Softwares

Projects

Generating customer service responses using Hugging face LLMs

Automated the process of responding to customer’s client support messages. The goal is to improve customer satisfaction and reduce the amount of time spent on customer support.
Designed a framework to connect a front-end chat system to a Hugging Face LLM using Streamlit.
Produced a Fine-tuned LLM with a large dataset (15 GB) and converted the response into an audio file using AWS Polly.
Scaled the system with Apache Kafka, AWS S3 and Redis – for faster access and reduced latency
Fine tuned the model on Google’s TPUs and hosted the rest of the framework on AWS, GitHub, and Redis Cloud.

Apache Kafka - Real-time Hate Speech analysis on Discord servers

Designed a framework to listen to messages on subscribed Discord servers and analyze the type of hate speech.
Scaled the system using Apache Kafka and Streamlit to accommodate multiple discord servers without changing any backend code.
Hosted the code on GitHub and Streamlit for ease of access and usage.

Trends in American’s Beliefs about Fluoride from Twitter

Conducted in-depth analysis of public sentiment regarding water fluoridation. Employing advanced techniques to extract 80,000 relevant tweets leveraging a Web Scraping tool via Digital Ocean VPC.
Collected a subset of 1000 tweets for manual labeling; Later used for fine tuning a Transformer model (RoBERTa).
Created a ML Pipeline to pre process the data, normalize and remove unnecessary tweets for finetuning the transformer model.
Analyzed the sentiment of 40,000+ tweets with the Fine-Tuned RoBERTa model, enabling effective predictions on a large volume of unlabeled data.
Developed correlation matrices by clustering topics derived from unstructured data sources.

Size Profile Optimization

Forecasting size level demand at each store for any set of store-option pair.
Using AI/ML methodologies to determine true demand and optimize inventory.
The forecast was created by consuming BI reports and SQL dumps.
A decision tree regressor was trained on historical sales data to understand trends and predict future sales.
A frontend was developed using Streamlit to host the deployed model.

Stock price prediction using past stock prices and tweets

Collected more than 5 years worth of stoick prices for the Alphabet stock ticker. Conducted predictive analysis on historical stock prices and public sentiment data to project future stock prices.
Explored and evaluated the performance of 9 different Machine Learning models and three word embedding techniques, namely TF-IDF and “Bag of Words” for analysis.
Implemented a data pipeline for daily Twitter data processing, normalization, and sentiment analysis.
Identified “Bag of Words” as the optimal word embedding model and Support Vector Classifier (SVC) as the most effective classifier.

Ensemble Machine Learning Model for sentiment analysis

Developed an ensemble Machine Learning model by combining two Deep Leaning models with TensorFlow and OpenAI; Utilized SpaCy and NLTK libraries to prepare the extracted data for seamless model training.
Utilized Digital Ocean VPCs to establish connections with multiple data centers worldwide, allowing for the simultaneous extraction of terabytes of tweets for data acquisition.
Orchestrated a robust data pipeline utilizing SpaCy and NLTK libraries to preprocess and prepare the extracted data for seamless model training.
Evaluated the model with Accuracy, MCC Coefficient and other ML metrics to reveal an impressive accuracy of 77% for ensemble model, while the existing state-of-the-art model achieved approximately 85%.

Data Mining and Machine Learning - Portfolio

Implemented various NLP techniques such as Naive Bayes, k-means clustering, hierarchical clustering, decision trees, and linear classifiers, all evaluated using a 10-fold cross-validation approach.
Employed a comprehensive set of evaluation metrics, including Accuracy, F-Score, ROC/AUC curve, precision, and recall, to assess the effectiveness of each model.

Volunteering & Student Clubs

HW Tech Club
Design Director (May 2021 - Jun 2022)

Managed a team of 5 students, providing guidance and mentorship on UI/UX design principles and tools.
Organized and executed a university-wide competition for the best UI/UX frontend website, promoting creativity and innovation among students.
Stayed up-to-date on the latest UI/UX trends and technologies, and shared knowledge with the team through regular presentations and discussions.
Fostered a positive and supportive team environment, encouraging collaboration and creativity.

Cyber Security Analyst (Oct 2020 - Jun 2022)
Developed and maintained a Virus scanner application using Python which checks for potential scamming websites via a chrome extension.
Hosted and delivered educational YouTube talks to promote awareness on different types of Wireless Hacking and OSINT Technologies.
Collaborated with other Tech Club members to organize and execute cybersecurity workshops and events.
Kept up-to-date with the latest cybersecurity trends and technologies, and shared this knowledge with the Tech Club community.
Provided cybersecurity support and guidance to Tech Club members and other students.

Creatives and Video Editor (Jul 2020 - May 2021)
Created and edited engaging videos to promote the Tech Club’s events and initiatives.
Collaborated with other creatives to develop and produce video content that was both informative and entertaining.
Managed the Tech Club’s social media accounts and used video to create a strong online presence.
Analyzed video performance data to identify areas for improvement.
Stayed up-to-date on the latest video editing trends and technologies.

The Uplift Foundation (Jul 2020 - Jun 2021)
Graphic Designer
Created brand guidelines for posting consistent content on social media accounts
Spearheaded a team of 4 people to convert text to interative and eye-catching content.

Blog

Predicting stock prices — a sentiment analysis approach
- Medium Blog
Apache Kafka — Real-time Hate Speech analysis on Discord servers
- Medium Blug