Data Engineer – Classical Statistics & Machine Learning
BLN24 · McLean, VA
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Jun 30, 2026
McLean, VA
Jul 21, 2026
What this job asks for AI summary
A hybrid data engineering and data science role supporting a federal statistical agency's platform modernization effort. Day-to-day work spans building and maintaining ETL/ELT ingestion pipelines within a cloud lakehouse architecture, and applying statistical methods and machine learning — including anomaly detection, regression, and time-series analysis — to operational data. Suits a mid-level practitioner equally at home writing production pipeline code and designing or validating analytical models, with experience navigating federal data sensitivity requirements.
Mid level · 3+ years · Washington-Arlington-Alexandria, DC-VA-MD-WV · Contract
“or” means any one of them counts — you don't need all of them.
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 35 people in the Washington-Arlington-Alexandria, DC-VA-MD-WV area plausibly meet what this posting asks for (database architects). range 10–50
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 $166,452 (middle half $130,866–$200,954).
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 (9)
This role is a genuine hybrid of data engineering (pipeline/ETL work) and data science (statistical modeling, ML). The primary SOC is 15-1243 (Database Architects) for the pipeline/lakehouse engineering emphasis, but 15-2051 (Data Scientists) is a strong runner-up given the explicit ML and classical statistics responsibilities.
The posting explicitly states 'contract position supporting a federal agency data modernization engagement', so employment type is Contract.
A Bachelor's degree is listed as required but the JD immediately qualifies it with 'or equivalent experience', so the degree requirement is set to None.
The JD requires U.S. citizenship and ability to obtain a public trust or other suitability determination. This is framed as an ability-to-obtain condition rather than a hard gate on holding an active clearance, so the clearance requirement is set to None. Hiring managers should note this citizenship/suitability requirement.
Total experience is stated as '3–5 years'; the minimum (3) is used for the overall years minimum.
Databricks, Spark, Delta Lake, Airflow, R, and SAS all appear under the Preferred Qualifications section.
The role is described as hybrid (not fully remote); remote is set to false. The posting notes that remote working may be allowed depending on the project, but the primary engagement is hybrid for a federal agency.
No compensation figures are provided in the posting.
Posting is for a contract engagement — the market benchmarks below price full-time roles, so read the comp comparison with that in mind.
Read the full posting
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