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Open nowFirst seen 40 hours ago

Senior Computational Scientist

ECS FEDERAL LLC255 open roles

Where
Springfield, VA, USA
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Your applicationOpen nowSenior Computational ScientistECS FEDERAL LLC · Springfield, VA, USA

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. ECS FEDERAL LLC postings stay open a median of 2 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: first seen 40 hours ago

ECS FEDERAL LLC median: 2 days open

The posting

Everforth ECS is seeking a Senior Computational Scientist to work in our Springfield, VA customer site and Fairfax, VA corporate site.

Everforth ECS is seeking a highly skilled and visionary Senior Computational Scientist lead the development, scaling, and deployment of advanced mathematical, statistical, and computational models. In this role, you will bridge the gap between complex theoretical science, Artificial Intelligence/Machine Learning (AI/ML), and high-performance computing (HPC) engineering. You will design robust algorithms, optimize high-performance codes, and lead cross-functional research initiatives that directly support our critical national security and defense mission datasets.

As a Senior Computational Scientist, you will leverage statistical and AI/ML algorithms to deliver advanced analytics, including predictive analysis and modeling, pattern-of-life analysis, and remote sensing change detection. You will manage the entire computational algorithm development lifecycle from design and training to deployment and maintenance while ensuring performance, observability, and security. This role contributes to building scalable infrastructure, integration layers, real‑time dashboards, and automated pipelines that enable secure, compliant, and efficient AI operations aligned with mission and business goals.

Key responsibilities include:

  • Design, implement, and validate complex computational models and simulations
  • Apply advanced machine learning, deep learning, and statistical physics methodologies to large-scale, structured and unstructured datasets
  • Optimize, parallelize, and scale scientific software across hybrid GPU/CPU cluster architectures
  • Lead end-to-end data science initiatives, encompassing the design, training, and production deployment of AI/ML algorithms
  • Partner with domain experts (aerospace, cybersecurity, intelligence) to translate mission needs into computational requirements
  • Write white papers, proposals, and technical documentation. When possible, publish in peer-reviewed journals
  • Mentor junior computational scientists, engineers, and data analysts on scientific software best practices

Salary Range: $180,000-250,000

General Description of Benefits

  • Must be a US Citizen
  • Active Top Secret / Sensitive Compartmented Information Clearance with CI Poly eligibility
  • Ph.D. or Master’s degree in Computational Science, Applied Physics, or Electrical Engineering
  • 5 to 8+ years of post-Ph.D. experience leading computational science initiatives preferably within defense, national laboratories, or advanced aerospace/computing industries
  • Mastery of high-performance scientific programming languages (e.g., Python, C++, Java, Matlab, etc.)
  • Proven ability to conduct advanced data analysis and apply data science methodologies for predictive modeling, pattern of life analysis, and change detection analysis
  • Extensive hands-on experience developing in Linux/Unix environments (Bash/Csh/Awk/Perl), using modern CI/CD software pipelines (such as GitLab), and containerization (Docker/Kubernetes)
  • Strong expertise in AWS cloud services (compute, storage, networking, IAM)
  • Deep technical expertise in parallel programming models (e.g., CUDA, cuDNN)
  • Strong foundation in AI/ML algorithms and ability to implement agentic workflow with MCP and prompt engineering
  • Experience in large language model (LLM) applications
  • Exceptional ability to synthesize highly abstract mathematical concepts into actionable, BLUF-style executive briefings for non-technical stakeholders
  • Strong understanding of model evaluation metrics (e.g., precision, recall, AUC) and statistical drift detection methods.
  • Experience with time-series databases, spatial databases, Resource Description Framework (RDF) databases, and relational databases
  • Strong communication skills with the ability to interface and collaborate with project managers, stakeholders, vendors, and technical staff
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