PYTHON DEVELOPER FOR PREDICTIVE ANALYSIS LINEAR REGRESSION AND SQL SERVER INTEGRATION

We are looking for an experienced Python developer to help us implement a predictive analysis process using historical sales data.
The goal is to forecast future sales for the next 8 weeks based on sales data from the past few weeks.
The predictions should use linear regression or any other suitable technique that fits the data.
The project will involve the following key components.
The project must be completed by January .
Please ensure that you can commit to this deadline before applying.
Key Responsibilities.
Data Analysis and Model Development.
You will use Python to create a predictive model that forecasts sales (measured in kilograms) for the next 8 weeks.
The model will use sales data from the previous 4 weeks to predict future sales.
Week 1 prediction.
Uses the previous 4 weeks of historical sales data.
Week 2 prediction.
Uses 3 weeks of historical sales data + Week 1 prediction.
Week 3 prediction.
Uses 2 weeks of historical sales data + Weeks 1 and 2 predictions.
This process will continue for up to 8 weeks into the future.
Data Integration.
The data will be extracted from a SQL Server database.
The Python script should connect to SQL Server, retrieve the necessary historical sales data, and store the output predictions back into a SQL Server database.
CSV Testing.
For the initial testing phase, you will be provided with a sample CSV file containing historical sales data.
The final version of the code should be able to handle SQL Server connections for real-time data retrieval.
Accuracy Requirement.
The results will be acceptable if the model can demonstrate a reasonable level of prediction accuracy, with a prediction error within a % margin compared to actual sales data.
The exact acceptable error margin may vary depending on the business context and the data itself, but a reasonable demonstration of predictive accuracy is required.
If you believe that a higher level of accuracy can be achieved, please provide evidence of that.
Output Specification.
The output should include the following columns for each prediction.
Year Week Predicted kilos (sales volume) Company Variety Mix Customer group Team Fresh Brand Prediction Process.
The script should automatically identify the latest year and week in the database and generate predictions for the next 8 weeks.
Additionally, a configuration setting (either a text file or a table entry) will allow us to specify a base week for predictions.
For example, if the data is available until week 40 and we specify a prediction range until week 30, the model should only use data up to week 29.
The code will keep the different versions and add the new predictions to be able to compare.
Additional Fields.
Each prediction should include the following metadata.
Prediction date First week predicted Method used for prediction Code Ownership and Execution.
The code must be open-source, and we will retain full ownership of the code and all deliverables.
The Python script should be executable on a Windows server, ideally packaged as an executable file (.
xe) for ease of use.
The code should be well-documented for future use and modifications.
Skills Required.
Strong experience with Python, particularly in data analysis and predictive modeling.
Experience with SQL Server integration using Python (e.
., using libraries like pyodbc or sqlalchemy).
Familiarity with linear regression and other predictive modeling techniques.
Ability to work with large datasets and optimize for performance.
Clear communication skills and the ability to understand business needs.
Additional Notes.
We are looking for a freelancer who can help with this project now and potentially future projects.
The project will be divided into phases, with an initial testing phase using a CSV file and later integrating with SQL Server.
If you have any questions or need further clarification, feel free to reach out.
ATTACHED YOU HAVE THE DATASET Big Data Sales Machine Learning (ML) Microsoft SQL Server Python Estatísticas ID do Projeto.
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