AI Driven Job Role Prediction and Recommendation Workflow

Intelligent Job Role Prediction and Recommendation

1. Data Collection

1.1. Identify Data Sources

Gather data from various sources such as:

• Employee resumes
• Job descriptions from pharmaceutical companies
• Industry reports and labor market trends
• Online professional networks (e.g., LinkedIn)

1.2. Data Aggregation

Utilize AI-driven tools like Tableau or Power BI to aggregate and visualize data for better insights.

2. Data Preprocessing

2.1. Data Cleaning

Implement natural language processing (NLP) techniques to clean and standardize data, removing duplicates and irrelevant information.

2.2. Feature Extraction

Extract relevant features from job descriptions and resumes using AI tools like spaCy or NLTK.

3. Job Role Prediction Model Development

3.1. Model Selection

Choose appropriate machine learning algorithms such as:

• Decision Trees
• Random Forest
• Neural Networks

3.2. Model Training

Utilize platforms like TensorFlow or PyTorch to train models on historical job data.

4. Job Role Recommendation Engine

4.1. Algorithm Development

Develop algorithms that recommend job roles based on user profiles and predicted skills.

4.2. Integration of AI Tools

Incorporate AI-driven products like IBM Watson Career Coach to enhance the recommendation process.

5. User Interface Design

5.1. Dashboard Creation

Create a user-friendly dashboard using tools like Figma or Adobe XD to present job role predictions and recommendations.

5.2. User Feedback Mechanism

Implement feedback loops to refine recommendations based on user interactions and satisfaction.

6. Continuous Improvement

6.1. Performance Monitoring

Regularly monitor model performance using metrics such as accuracy, precision, and recall.

6.2. Model Updates

Update models periodically with new data to ensure relevance and accuracy using automated tools like MLflow.

7. Reporting and Analytics

7.1. Generate Reports

Utilize reporting tools like Google Data Studio to create insights on job market trends and predictions.

7.2. Stakeholder Communication

Communicate findings and recommendations to stakeholders through regular presentations and reports.