Employee Attrition Predictive Model Development
Budget: ₹750 – ₹1,250 INR
I'm looking for a skilled data scientist to develop a predictive model for analyzing and forecasting employee attrition in my organization. The primary goal of this project is to gain insights that can help improve our HR strategies.
Key responsibilities include:
- Data collection & preprocessing: Utilizing the numerical and categorical data we have on employee metrics.
- Exploratory Data Analysis (EDA): Understanding the data at hand and uncovering potential patterns.
- Feature Engineering: Identifying the most relevant variables for our model.
- Model Development: Using various classifiers including SVM, DecisionTreeClassifier, RandomForestRegressor, RandomForestClassifier, and KNeighborsClassifier.
- Model Evaluation: Assessing the accuracy of the models and selecting the best one.
- Deployment: Implementing the model using Flask and Pickle for local server integration.
- Reporting: Providing comprehensive insights, with a specific focus on department-wise attrition analysis.
The ideal freelancer for this project should have:
- Proficient skills in data science and HR analytics.
- Experience in using the specified models.
- Ability to deploy models using Flask and Pickle.
- Excellent reporting skills, particularly in providing insights for HR strategy improvements.
The best accuracy in my previous attempts was achieved with the KNeighborsClassifier. I am looking for a comprehensive, detailed and insightful analysis that can help us enhance our HR strategies. You can find my previous work on this project here: https://github.com/AyanBiswas1997/Hr_Analyst.
Key responsibilities include:
- Data collection & preprocessing: Utilizing the numerical and categorical data we have on employee metrics.
- Exploratory Data Analysis (EDA): Understanding the data at hand and uncovering potential patterns.
- Feature Engineering: Identifying the most relevant variables for our model.
- Model Development: Using various classifiers including SVM, DecisionTreeClassifier, RandomForestRegressor, RandomForestClassifier, and KNeighborsClassifier.
- Model Evaluation: Assessing the accuracy of the models and selecting the best one.
- Deployment: Implementing the model using Flask and Pickle for local server integration.
- Reporting: Providing comprehensive insights, with a specific focus on department-wise attrition analysis.
The ideal freelancer for this project should have:
- Proficient skills in data science and HR analytics.
- Experience in using the specified models.
- Ability to deploy models using Flask and Pickle.
- Excellent reporting skills, particularly in providing insights for HR strategy improvements.
The best accuracy in my previous attempts was achieved with the KNeighborsClassifier. I am looking for a comprehensive, detailed and insightful analysis that can help us enhance our HR strategies. You can find my previous work on this project here: https://github.com/AyanBiswas1997/Hr_Analyst.