- SQL (PostgreSQL) & NoSQL (MongoDB - pymongo)
- Data Cleaning, Data Analysis, EDA, Data Visualization with Python (numpy , pandas , matplotlib ,seaborn , dash)
- Machine Learning (Deep learning, Regression algorithms, classification algorithms, scikit-learn , keras, tensorflow)
- Tableau Desktop Specialist certified
- AWS Solutions Architect Associate
- PowerBi
- Excel (pivots, index & match)
- WebScraping with Python (BeautifulSoup)
- DataBricks, pyspark
- Database communication (psycopg2, sqlalchemy)
- Market Segmentation via RFM analysis, cohort analysis
- Market Basket Analysis (arules)
- Creating a supervised learning diagnostic for classifying Berlin AirBnb listings likely to get top 5% rating
- Detecting ideal clusters from imdb's movie dataset to segment using unsupervised learning
- Kaggle Submission, using XGBRegressor with shap, grid search and hyperopt to predict house prices
- Masters in Big Data Engineering & Data Science
- Data Science Bootcamp (500 hours)
- Exposure to git version control, querying (SQL & MongoDB), data cleaning/ preparation & analysis (numpy & pandas), visualization (seaborn, matplotlib,PowerBi,dash), deep learning and supervised machine learning and unsupervised machine learning models (regression & classification via sklearn,keras,tensorflow).
- Bachelor of Business Administration - BBA, Business Administration and Management, General (Marketing Major)
- Coordinated new launches & telco operator migrations involving up to four technical departments.
- Active involvement in new product launch (spec creation & updating, api integrations briefing, UAT creation, health check overview, quality control & assurance and reporting suggestions).
- Created & lead client presentations and interactive workshops to provide an engaging story-telling experience with actionable insights.
- Created excel attribution model to evaluate quality of TVC spot recruitment
- Created RFM model to segment database and identify churn risks.
- Set and organized quarterly/monthly/weekly tech pipeline
- Constructed monthly communication plan (sms promotion, digital advertising)
- 20% increase in quality spot recruitment despite 30% airtime reduction
- Telco operator launches & migrations with minimum downtime & minute post launch issues
- 20% reduction in deadline misses in major tech deliverables and 40% for mid importance/operational tech deliverables.
- 15% decrease in year-on-year optout via effective RFM targeting.
- Using boto3 sdk to access Amazon s3 to download photos
- Creating scripts to categorize photo status based on csv information files
- Using google collab to run custom convolutional neural network and transfer learning network Achievements
- Constructed three separate CNN’s capable of detecting furnished apartment status (90% accuracy), renovated status (70%), room type (70%)