Stock Market Trend Prediction Using ML - Basic level study for factors influencing

I'm looking for a data scientist to help predict stock market trends using machine learning. The project involves time series prediction and classification using models such as LSTM, Random Forest, and Decision Tree.

Key Responsibilities:
- Utilizing Python to implement the models
- Conducting statistical analysis on the provided time series data
- Training and testing the models based on different time frames

Ideal skills for this job include:
- Proficiency in Python and machine learning libraries such as PyTorch and TensorFlow
- Experience with time series analysis
- Strong understanding of LSTM, Random Forest, and Decision Tree models
- Capable of performing statistical analysis using R, SPSS, or Stata

The data for this project is attached and includes Y1 and Y2 as targets, with features represented by 'abc'. The distance from the date to the expiry date will also contribute to sentiment and timing.

You will have two options for the training and testing of the data:
- Option 1: Train on data from 9:30 AM to 1 PM, and test from 1 PM to 3 PM.
- Option 2: Train on two months of data, and test on one month of data.

Please note that the primary goal of this project is to predict stock market trends.