Data Analyst
Summary
Implemented a delivery day estimation system by extracting more than 18 million rows of the clients retail data from AWS S3 buckets and analyzing it in Tableau and MySql which incremented the estimation of delivery days accuracy by more than 85%.
Improved the package delivery status system by building a machine learning model that predicted the delivery status from the clients retail data using the XGBOOST algorithm and achieved an accuracy of more than 91%.
Led a team of 4 to implement the automation of more than 5 modules like Expenses, Billing, Payables, Receivables, etc. in PeopleSoft using Peoplesoft Test Framework which expedited the testing process via 3 folds time.
Developed an interactive dashboard to track the number of repetitive tickets regarding clients issues in PeopleSoft pages using Tableau that led to the automation of those issues improving the ticket analyzing efficiency by 40%.
Developed complex reporting solutions enabling the client to generate reports using
Expectations
Mentorship, Flexible
Employment Preferences
Expected Base Salary
**,000 USD
Academic Degree
Experience
Total Professional Experience
Startup Experience
Big-Tech Companies
Skills
- Python
- R
- SQL
- Oracle Peoplesoft
- Shell Scripting
- HTML5
- CSS3
- JavaScript
- Tableau
- Power BI
- Jira
- ServiceNow
- Advanced Excel
- GSuite
- K-NN
- Linear
- Logistic Regression
- Decision Tree
- Support Vector
- SVM
- Neural Networks
- Random Forest
- Gradient Boosting
- Ridge
- Lasso Regression
- CNN
- RNN
- Hadoop
- Hive
- Impala
- Spark
- Flume
- Hibernate Query Language
- MySQL
- NoSQL
- Mongo DB
- Oracle10g
- 11G
- 12C
- TensorFlow
- Keras
- PyTorch
- Pandas
- NumPy
- Matplotlib
- Scikit-Learn
- OpenCV
- NLTK
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