Data Scientist / Machine Learning Engineer

ARLINGTON, VA, US • Posted 1 hour ago • Updated 1 hour ago
Full Time
On-site
USD $160,000.00 - 185,000.00 per year
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Software Development
  • Predictive Analytics
  • Unstructured Data
  • Data Analysis
  • EDA
  • Statistical Models
  • Deep Learning
  • Forecasting
  • Natural Language Processing
  • Computer Vision
  • Scalability
  • Machine Learning Operations (ML Ops)
  • Production Engineering
  • Training
  • Continuous Integration
  • Continuous Delivery
  • Clustering
  • Documentation
  • Data Engineering
  • Business Process
  • Data Processing
  • Data Quality
  • Regulatory Compliance
  • Microsoft Azure
  • Amazon SageMaker
  • Databricks
  • Vertex
  • Workflow
  • Distributed Computing
  • Analytics
  • Collaboration
  • Use Cases
  • Emerging Technologies
  • Research
  • Security Clearance
  • Computer Science
  • Mathematics
  • Advanced Analytics
  • Algorithms
  • Data Modeling
  • Python
  • SQL
  • Data Manipulation
  • Cloud Computing
  • Problem Solving
  • Conflict Resolution
  • Analytical Skill
  • Communication
  • Data Science
  • Machine Learning (ML)
  • Statistics
  • Generative Artificial Intelligence (AI)
  • Large Language Models (LLMs)
  • Risk Management
  • Health Care
  • Finance
  • SAP BASIS
  • Law
  • Artificial Intelligence
  • Cyber Security
  • Partnership
  • Innovation
  • Accountability

Summary

Job Description

Everforth ECS is seeking a Data Scientist/Machine Learning Engineer to join our team in Arlington, VA (Hybrid) . This position is contingent upon award.

We are seeking a talented Data Scientist / Machine Learning Engineer to design, develop, deploy, and optimize advanced analytics and machine learning solutions that drive business insights and operational efficiencies. This role combines data science, machine learning engineering, and software development to transform complex data into scalable, production-ready AI and predictive analytics solutions.

The ideal candidate will possess expertise in statistical analysis, machine learning algorithms, AI/ML-assisted clustering, feature engineering, model deployment, anomaly detection, and cloud-based AI platforms while collaborating closely with business stakeholders, data engineers, and technology teams.

Key Responsibilities

Data Science & Advanced Analytics
  • Analyze structured and unstructured data to identify trends, patterns, and actionable insights.
  • Develop predictive, prescriptive, and classification models to support business objectives.
  • Perform exploratory data analysis (EDA), feature engineering, and statistical modeling.
  • Design experiments and evaluate model performance using appropriate statistical methodologies.
  • Present findings and recommendations to technical and non-technical stakeholders.
  • Support efforts in anomaly detection.
Machine Learning Development
  • Design, build, train, and optimize machine learning and deep learning models.
  • Develop solutions for forecasting, anomaly detection, natural language processing (NLP), recommendation systems, and computer vision applications.
  • Evaluate and select appropriate algorithms based on business requirements and performance objectives.
  • Continuously improve model accuracy, scalability, and maintainability.
MLOps & Production Engineering
  • Deploy machine learning models into production environments.
  • Build automated model training, validation, deployment, and monitoring pipelines.
  • Implement CI/CD practices for machine learning workflows.
  • Support AI/ML-assisted clustering efforts.
  • Monitor model performance and address model drift, data drift, and operational issues.
  • Maintain model governance, versioning, and documentation standards.
Data Engineering & Platform Integration
  • Collaborate with data engineers to develop scalable data pipelines and feature stores.
  • Integrate machine learning solutions into enterprise applications and business processes.
  • Optimize data processing workflows for large-scale datasets.
  • Ensure data quality, security, and compliance standards are maintained.
Cloud & AI Platforms
  • Develop and deploy solutions using cloud-native AI and machine learning services.
  • Leverage platforms such as Azure Machine Learning, AWS SageMaker, Databricks, Vertex AI, or equivalent technologies.
  • Perform multi-source summarization with human-review workflow by combining AI-driven aggregation of diverse sources with targeted human validation.
  • Utilize distributed computing frameworks to support large-scale analytics workloads.
  • Support enterprise AI strategy and modernization initiatives.
Collaboration & Innovation
  • Partner with business leaders to identify opportunities for AI and advanced analytics solutions.
  • Translate business requirements into machine learning use cases and technical requirements.
  • Stay current on emerging technologies, AI trends, and industry best practices.
  • Contribute to innovation initiatives, proofs of concept, and research activities.
Salary Range: $160,000 - $185,000

General Description of Benefits

Required Skills

  • Top Secret Clearance
  • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
  • 5+ years of experience in Data Science, Machine Learning Engineering, Artificial Intelligence, or Advanced Analytics.
  • Strong understanding of machine learning algorithms, statistical analysis, and data modeling techniques.
  • Experience building and deploying machine learning models in production environments.
  • Proficiency in Python and machine learning libraries/frameworks.
  • Strong knowledge of SQL and data manipulation techniques.
  • Experience working with large datasets and cloud-based data platforms.
  • Excellent problem-solving, analytical, and communication skills.


Desired Skills

  • Master's degree in Data Science, Machine Learning, Artificial Intelligence, Statistics, or related discipline.
  • Experience with Generative AI and Large Language Models (LLMs).
  • Familiarity with Retrieval-Augmented Generation (RAG) architectures.
  • Experience supporting enterprise AI transformation initiatives.
  • Knowledge of model governance, responsible AI, and AI risk management frameworks.
  • Experience working in highly regulated industries such as healthcare, finance, government, or defense.
#EverforthECS1

ECS Federal LLC is an equal opportunity employer and does not discriminate or allow discrimination on the basis any characteristic protected by law. All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, or local jurisdiction law.

Everforth ECS is the federal segment of Everforth , a $4B global organization with over 10,000 employees. Our nearly 3,500 professionals deliver advanced technology solutions in data and AI, cybersecurity, and enterprise transformation, serving defense, intelligence, and federal civilian agencies.

Our work powers mission-critical outcomes, strengthens technology partnerships, and creates meaningful opportunities for our people. We are defined by a commitment to excellence in delivery, a culture of innovation, and an environment where talent can thrive and grow.

We value:
  • Attracting and developing top talent and high-performing teams
  • Fostering a culture that is engaging, accountable, and mission-driven

Meet the challenge. Make a difference with Everforth ECS!
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 10112MAN
  • Position Id: 5046
  • Posted 1 hour ago
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