Senior Data Scientist

KIBO is a registered United States company dedicated to providing governments worldwide its services of inspection, analysis, certification, and compliance.

The Senior Data Scientist owns the analytics engine behind KIBO's service — the price-verification benchmarking and the risk-scoring that turn import-declaration data and international trade data into defensible, inspection-ready outputs and the reporting delivered to the customs administration. It is the pivotal quantitative role, and includes building the customs-revenue baseline analysis that underpins the program.

• Data integration. Build and maintain pipelines that ingest customs declaration data (ASYCUDA/SYDONIA) and commercial international trade-price data, reconciling schemas, units and currencies into a single analytical warehouse.
• Price-verification analytics. Construct the benchmarking that compares declared values against international reference prices — surfacing likely under-invoicing while respecting the WTO Customs Valuation framework — and document the method so findings are defensible.
• Risk scoring. Design, train and monitor the models and rules that score declarations for anomalies in value, tariff classification and origin, and that prioritize shipments for inspection.
• Revenue-baseline analysis. Produce the customs-revenue baseline analysis used to establish reference metrics with the authorities.
• Generate the recurring risk-assessment reports and the monthly reporting delivered to the customs administration, with clear, auditable lineage from source data to conclusion.
• Feedback loop. Incorporate field-inspection results back into the models to improve hit-rates over time.

• 5+ years of experience in data science, quantitative analytics, applied statistics, or machine learning, including production experience building models and data pipelines using real operational data.
• Strong Python and SQL skills, with hands-on experience using tools such as pandas, scikit-learn, or equivalent analytical/modeling libraries.
• Experience with anomaly detection, statistical benchmarking, supervised or unsupervised modeling, model monitoring, and performance evaluation.
• Demonstrated ability to work with large transactional, logistics, financial, trade, or similarly complex operational datasets, including reconciling heterogeneous sources, schemas, units, and currencies.
• Ability to clearly document analytical methods, explain findings, and defend quantitative outputs to non-technical stakeholders, auditors, or government counterparts.
• Strong data-governance practices, including reproducibility, data lineage, version control, quality checks, and appropriate handling of sensitive data.

• Exposure to customs, international trade, tariff/HS classification, import/export data, valuation, or commercial trade-price data.
• Familiarity with ASYCUDA/SYDONIA data structures or other customs, logistics, or government data systems.
• Experience standing up analytics capabilities in data-constrained, emerging-market, public-sector, or operationally complex environments.
• Experience with cloud data warehouses and workflow orchestration tools such as Snowflake, Big Query, Redshift, Airflow, dbt, Prefect, or similar platforms.

• Stand up the analytical environment and ingest initial customs and trade-data samples.
• Deliver an initial customs-revenue baseline analysis and prototype the price-verification benchmarking and risk-scoring.
• Produce the first risk-assessment reports that support inspection getting under way.

Reports to the Engagement / Delivery Lead; takes valuation-methodology guidance from the Customs & Valuation…