Proprietary Data Scoring Algorithm Development
Budget: $30 – $250 USD
Request details
FOR EXPERTS WITH EXTENSIVE EXPERIENCE IN THE FIELD ONLY
Objective: Scoring Algorithm for evaluating potential investments
Data Source: 200+ proprietary historical records with up to 90 parameters
Mentoring requested (to be worked with tech project lead and data engineer):
• Data-Preprocessing (missing values, normalization, outliers)
• Implementation methods for feature selection (e.g. correlation Analysis, feature importance, etc.)
• Identify and run different algorithms (e.g., logistic regression, decision trees, random forests, gradient boosting, neural networks)
• Details and rationale behind algorithms selection
• Hyperparameter tuning and optimization
• Cross-validation
• Performance metrics (e.g., accuracy, precision, recall, F1 score, ROC-AUC)
• Score Calculation and thresholds
• Deployment and Monitoring
Tools available:
• In use: Microsoft Fabric and Excel (VBA)
• Potential tools: Python, R
Timeframe: 1 month
FOR EXPERTS WITH EXTENSIVE EXPERIENCE IN THE FIELD ONLY
Objective: Scoring Algorithm for evaluating potential investments
Data Source: 200+ proprietary historical records with up to 90 parameters
Mentoring requested (to be worked with tech project lead and data engineer):
• Data-Preprocessing (missing values, normalization, outliers)
• Implementation methods for feature selection (e.g. correlation Analysis, feature importance, etc.)
• Identify and run different algorithms (e.g., logistic regression, decision trees, random forests, gradient boosting, neural networks)
• Details and rationale behind algorithms selection
• Hyperparameter tuning and optimization
• Cross-validation
• Performance metrics (e.g., accuracy, precision, recall, F1 score, ROC-AUC)
• Score Calculation and thresholds
• Deployment and Monitoring
Tools available:
• In use: Microsoft Fabric and Excel (VBA)
• Potential tools: Python, R
Timeframe: 1 month