Open to Data Science opportunities!
Hello there! Welcome to my Data Science portfolio.
I am a data analyst with graduate in M.Sc. Applied modelling and Quantative methods from Trent University. I have over 3 years of experience in data analytics and consulting in pharmaceutical domain, with focus on statistical data analysis and Business Intelligence. I have led led several projects on customer targeting, behaviour based segmentation and opportunity identification analyses for product launches. I am skilled in working with large datasets using Python, R, SAS, SQL, Excel and have proven track record managing operational processes and implementing improvements to automate tasks. Proeficient in extracting insights, developing stories and presenting to stakeholders at various levels.
I am driven to identify patterns and solve problems using data. Realizing the infinite possiblities present in data, I have always aimed to make data more accessible to the general user, implemeting ideas that help eliminate the tedious processes involved in obtaining data, and focus on extracting insights.
Led teams in high client exposure role. Collobarated with various stakeholders to develop business knowledge and presented analyses to senior leadership.
Customer targeting and segmentation, Product launch analytics, KPI tracking, Pre-post analyses
Experienced in developing and maintaining dynamic dashboards and visualizations with Excel, VBA, R Shiny and Tableau.
sk-learn, Pytorch Neural networks, EDA, Text cleaning, sentiment classification, NLTK
Classified sarcastic Tweets using word embeddings generated from BERT model. Implemented a framework to utilize general context from Glove embeddings with LSTM Neural network to improve classification accuracy
Trained a XGboost model using R to classify distress sentiment in Reddit posts. Deployed an interactive R Shiny dashboard which allows user to tweak input parameters and understand effects on the model and output.
Used NLP techniques to extract information from product descriptions. Used LightGBM and RandomForest classifier to identify product type, subtype and company type.