Business Intelligence Specialist
1 week ago
Data Analysis Expertise
We are building a cutting-edge platform that leverages data science and artificial intelligence to revolutionize agri-trade.
- Collect, clean, and preprocess vast datasets from multiple sources to inform business decisions.
- Design and implement advanced scoring algorithms to assess buyer/seller reliability and default risk.
- Engineer features from trade history, payment timeliness, disputes, cancellations, and external market data.
- Apply statistical models and machine learning techniques (logistic regression, random forests, gradient boosting, neural networks) to predict trustworthiness.
- Develop frameworks normalized to a range (e.g., 0-1000), similar to industry standards.
- Validate and back-test models against historical data to ensure accuracy, fairness, and stability.
- Build monitoring pipelines to track score performance, drift, and anomalies in real time.
- Collaborate with cross-functional teams to ensure scores align with practical trade and risk management requirements.
- Document methodologies and communicate insights to technical and non-technical stakeholders.
Requirements:
- Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Economics, or a related field.
- 2-5 years of experience as a Data Analyst, preferably in credit scoring, risk modeling, or fraud detection.
- Strong proficiency in Python (pandas, numpy, scikit-learn, statsmodels) or R.
- Experience with machine learning algorithms such as logistic regression, decision trees, random forests, gradient boosting (XGBoost/LightGBM), and neural networks.
- Strong SQL skills for handling large datasets; experience with data pipelines and API integrations.
- Domain knowledge of credit scoring principles, risk assessment, and regulatory considerations.
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