Senior Data Scientist
Securiport · Reston, VA
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Jul 15, 2026
Reston, VA
Jul 20, 2026
What this job asks for AI summary
This role centers on building and owning the quantitative core of a customs compliance service: data pipelines ingesting customs declaration and international trade-price data, price-verification benchmarking, anomaly-based risk scoring for import declarations, and recurring revenue-baseline and risk-assessment reports delivered to government customs authorities. It suits an experienced data scientist with a background in production modeling, statistical benchmarking, and working with complex operational datasets.
Senior level · 5+ years · Remote
“or” means any one of them counts — you don't need all of them.
Posted 2 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Roughly 1,250 people nationally plausibly meet what this posting asks for (data scientists). range 360–1,850
Applicant volume Moderate — A normal amount of company. The rare requirements below are what will separate a shortlisted application from the rest.
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $122,874 (middle half $87,544–$162,374).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (7)
No work location or metro area is specified in the posting. KIBO is a US-registered company and the role appears to be remote or field-deployed internationally (supporting customs administrations in emerging markets), but no specific city or country is stated. The metro and state fields are left blank accordingly.
The posting lists no degree requirement — none is stated as required or preferred.
The 'pandas, scikit-learn, or equivalent' phrasing appears under the Required Qualifications section; 'or equivalent' signals that specific tools are interchangeable, but the underlying Python-based analytical/modeling capability is a hard gate. scikit-learn is listed as the primary named modeling library with alternatives implied by 'equivalent analytical/modeling libraries' — no other specific library is named, so no alternatives are populated.
Snowflake, BigQuery, Redshift, Airflow, dbt, and Prefect all appear under Preferred Qualifications and are treated as nice-to-haves. Snowflake is listed as the primary cloud warehouse option with BigQuery and Redshift as named alternatives; Airflow is the primary orchestration tool with Prefect as a named alternative.
ASYCUDA/SYDONIA familiarity is listed under Preferred Qualifications and is treated as a nice-to-have despite being central to the role's data sources.
The alternative occupation runner-up (15-1243 Database Architects) reflects the significant data-pipeline and analytical-warehouse-building responsibilities, but the dominant work — ML modeling, risk scoring, anomaly detection, and statistical benchmarking — clearly points to 15-2051 Data Scientists.
This posting reads as a fully-remote role, so it was scored against the national candidate pool rather than a single metro.
Read the full posting
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