I'm a experienced data scientist with 4+ years of experience in computational modeling, data analysis, and machine learning. Currently, working as a data science/ data quality engineer, my role is to create and maintain robust data quality assurance processes, and design innovative data-driven products that empower the competitiveness of businesses in the home improvement retailer.
Work experience with data science engineering, data engineering, and data quality engineering:
- Work experience creating market share dashboards to allow clients gauge opportunities to improve their competitiveness.
- Work experience developing new data-driven products for retailers to boost their sales and keep track of their performance in the market.
- Experience developing and deploying machine learning models for demand forecasting and pricing.
- Work experience in implementing data QA practices on top of data pipelines and creating metrics to keep track of the health of end-of-pipeline data.
- Work experience in computational and statistical modeling.
Main work tools: Python/ PySpark | Databricks | SkLearn/ XGBoost/ PyTorch | SQL | Tableau | Streamlit/ Flask | Docker | AWS (Sage Maker, RedShift, EC2, S3) | Git | Linux
