As someone with a comprehensive background in data science, the internet, and real estate, I'm passionate about leveraging open data and customer recordings to develop novel insight into spatial opportunities/risks in demand and supply, operations, and more. I'm also interested in exploring big data and cloud ecosystems through data pipeline, machine learning, and visualization.
Market arear and visit prediction for Philadelphia Parks & Recreation
Programming Languages: Python, R, SQL, NoSQL, JavaScript, HTML
Tools: Tableau, Spark, MapReduce, AWS, GCP, Airflow, PyTorch, OpenAI, Pylogit, ArcGIS, GeoDa, AutoCAD, MS Excel
Technical Skills: Statistics, Machine learning, Hypothesis testing, A/B testing, ETL pipeline, Web scraping, Data visualization