2023 Data Science Job Market Analysis | Tools: SQL, Data Analysis, PostgreSQL
- 📊 Dive into the data job market! Focusing on data scientist roles, this project explores 💰 top-paying jobs, 🔥 in-demand skills, and 📈 where high demand meets high salary in data science.
Code
- Created Adversarial Search Nine Men’s Morris agent using Mini-Max and Alpha-Beta pruning algorithms with dynamically altering Mini-Max depth, achieving an 88% win rate against human players.
- Competed in a class-wide AI competition organized by the professor, securing a top 3 position among 80+ participants.
Code
- Built a deep learning model using Hugging Face T5 to generate counter-speech against online speech, with an accuracy of 85%.
- Evaluated the effectiveness of the generated counter-speech in mitigating negativity through sentiment analysis using TextBlob.
Code
- Conceived a scalable real-time Spark pipeline on AWS infrastructure for data ingestion, pre-processing, and stock prediction.
- Leveraged Databricks with PySpark to construct a model using LSTM-RNN achieving a squared error of 5% on historical data.
- Collaborated with a team of 3 students to refine the model, improving its accuracy to 93% through hyperparameter tuning.
Code
- Created databricks notebooks to ingest, transform, analyze and create reports on Formula 1 racing data.
- Written Spark SQL queries to find the dominant drivers and teams for visualization.
- Scheduled the pipeline using Azure Data Factory (ADF) for monitoring and alerts.
Code
- Led a team of 5 to analyze Airbnb’s impact on housing, completing the project on time.
- Utilized GeoPandas and ZCTA5 shapefiles to extract granular data at the zip code level.
- Created a scalable Tableau dashboard to assess risk for 1.5M Airbnb listings from state to zip code level.
