Senior Data Science Engineer (With TS/SCI Clearance and a current Full Scope Poly) at J&T Business Consulting
Annapolis Junction, MD
$245,000
Jul 26, 2026
Annapolis Junction, MD
Jul 27, 2026
What this job asks for AI summary
A senior-level role focused on building and operating end-to-end machine learning systems — from data pipelines and feature engineering through model training, deployment, and ongoing monitoring in production. The work spans MLOps practices, cloud infrastructure, and collaboration with cross-functional teams. It suits an experienced data scientist or ML engineer comfortable owning the full model lifecycle and guiding junior colleagues.
Senior level · 5+ years
“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
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)
Location is not specified in the posting; CBSA and state fields are left blank. Remote eligibility is also unstated — remote is set to false by default.
The degree requirement lists Bachelor's or Master's; since both are offered as alternatives and equivalent experience is not explicitly accepted, the minimum stated is a Bachelor's — however, the JD does not use hard gate language ('must have a degree'), so the degree requirement is set to None.
The 5–8+ years range is mapped to the overall years minimum of 5 (the lower bound of the stated range).
scikit-learn, TensorFlow, PyTorch, and XGBoost are listed together as interchangeable ML library options under Required Qualifications; scikit-learn is used as the primary with the others as alternatives.
Docker and Kubernetes are listed together under a single 'containerization and orchestration' requirement in the Required section; both are captured as separate required skills since they serve distinct functions (containerization vs. orchestration), though each lists the other as an alternative to reflect the joint framing.
Java, Scala, and C++ are listed as a 'plus' within the Required section ('one additional language… is a plus'), so they are marked as preferred despite appearing in that section.
Generative AI, LLMs, RAG, AI agents, MLOps tools, Kafka, and vector databases all appear under Preferred Qualifications.
Read the full posting
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