Exiger is seeking a Data Scientist to drive mission-focused analytics in customs and trade enforcement, applying technical innovation to strengthen enforcement, optimize tariff revenue, and mitigate supply chain risk.
Requirements
- Advanced proficiency in Python (pandas, NumPy, scikit-learn, TensorFlow/PyTorch), SQL, and applied statistics.
- Strong background in machine learning, including anomaly detection, classification, clustering, and predictive analytics.
- Experience with LLMs (development, fine-tuning, applied use cases in classification and text analysis).
- Knowledge of tariff classification, customs valuation, origin determination, and the Harmonized Tariff Schedule (HTSUS).
- Understanding of transshipment rules, including substantial transformation, and ability to detect compliance risks in diverted/misclassified shipments.
- Familiarity with U.S. trade compliance frameworks.
- Proficiency in data visualization tools (Tableau, Power BI, matplotlib, seaborn) to deliver insights and decision support.
Responsibilities
- Develop and apply machine learning (ML) and natural language processing (NLP/LLM) models to support customer needs.
- Conduct statistical and econometric analysis of large-scale customs and trade datasets to identify anomalies, fraud risks, and tariff revenue optimization opportunities.
- Build predictive risk models to prioritize shipments for review based on compliance, diversion, or misclassification indicators.
- Perform tariff and trade flow analysis to support classification accuracy, customs valuation, and duty collection forecasting.
- Design and maintain dashboards, reports, and data visualizations to communicate findings to customers.
- Collaborate with AI Solutions Engineers to ensure analytical models are operationalized within customer systems and data pipelines.
- Present results and technical findings in clear, mission-focused language for enforcement, compliance, and policy stakeholders.
Other
- Strong communication skills to translate complex analytical outputs into actionable insights for customers.
- Ability to work collaboratively with engineers, analysts, and mission operators to align data science outputs with operational enforcement goals.
- Flexible, hybrid approach to working from home and in the office where applicable.
