Work Experience

Feb 2022 - Current

I work in the cloud supply chain sustainability team as a data and applied scientist
I design patterns for data flow between systems for reliable cloud supply chain data

Dec 2019 - Feb 2022

Engineering

Machine learning

Developed a classification model to categorise financial transaction and predict transaction categories
Developed a classification model to find website that solely exist to boost the ranking of target websites in search engines

Dec 2017 - Nov 2019

Developed tree-based machine learning models for user segmentation and classification that resulted in a 30% increase in the revenue across projects
Developed machine learning models for revenue forecasting and risk assessment
Implemented new frameworks like firebase for better data collection, spark for processing bigger datasets
Developed play store scrapers to find the best keywords for data-driven app store optimization
Conducted statistical data analysis on user data to improve key business metrics like day 1 retention, from 12% to 25%
Created data visualization dashboards and decreased the product turnaround time by 40%
Improved user engagement by carrying out data-driven A/B experiments
Developed ETL pipelines for processing the clicks and interactions data of users
Optimized queries to reduce the costs incurred in querying data from bigquery

Technical Skills

Languages: Python, R, C++, Java, SQL
Frameworks: Pytorch, PySpark, Keras, Fastai, Pandas, Numpy, Sklearn, Plotly, Matplotlib, SparkML, nltk, SpaCy
Technologies: Bash, Git, UNIX, Google Cloud, AWS, IBM Cloud
Databases: MySQL, SQLite, MongoDB, HDFS, Amazon Data lake, BigQuery, IBM object storage