Senior Data Science Engineer (With TS/SCI Clearance and a current Full Scope Poly)

J&T Business Consulting; Maryland; On-site; USD 130,000 - 210,000; Full time

Job summary

J&T Business Consulting in Annapolis Junction, MD, is seeking a Senior Data Science Engineer with TS/SCI clearance to design, train, and deploy ML models in production, and to build scalable data pipelines.

You will own end-to-end ML workflows, collaborate with cross-functional teams, ensure data quality and security, and mentor junior staff while staying current with cloud technologies.

Experience 5–8+ years and strong Python, SQL, and ML frameworks are required.

Qualifications

• Bachelor's or Master's degree in CS/DS/Math/Engineering or related field.
• 5–8+ years of data science, ML, or AI engineering experience.
• Strong Python (required); SQL and one other language (Java/Scala/C++) a plus.
• Experience with ML libraries such as scikit-learn, TensorFlow, PyTorch, XGBoost.
• Proficiency in data processing frameworks like Spark or Hadoop.
• Experience deploying ML models on cloud platforms (AWS/Azure/GC).
• Familiarity with Docker, Kubernetes, Git, CI/CD and DevOps practices.

Responsibilities

• Design, build, and deploy machine learning models and data science solutions in production.
• Develop scalable data pipelines for ingestion, transformation, and feature engineering.
• Build and maintain end-to-end ML workflows including training, evaluation, deployment, and monitoring.
• Analyze large structured and unstructured data to identify trends and opportunities.
• Collaborate with product managers, engineers, and stakeholders to define data-driven solutions.
• Optimize ML algorithms for performance, scalability, and reliability.
• Implement MLOps, including CI/CD pipelines, model versioning, testing, and monitoring.
• Ensure data quality, governance, security, and compliance with standards.
• Mentor junior data scientists and engineers through technical guidance and code reviews.
• Stay current with AI, ML, and cloud tech and recommend innovative solutions.

Skills

Python

SQL

Java/Scala/C++

ML algorithms & modeling

Statistics & modeling

Data pipelines

CI/CD practices

GIT

Cloud platforms (AWS/Azure/GC)

MLOps concepts

Education

Bachelor's or Master's degree in CS/DS/Math/Engineering

Tools

Docker

Kubernetes

Spark

Hadoop

TensorFlow/PyTorch/XGBoost

MLflow/Kubeflow

SageMaker/Vertex AI/Azure ML

Job description

Senior Data Science Engineer (With TS/SCI Clearance and a current Full Scope Poly)

Annapolis Junction, United States | Posted on 08/20/2026

• Design, build, and deploy machine learning models and data science solutions in production.
  
• Develop scalable data pipelines for data ingestion, transformation, and feature engineering.
  
• Build and maintain end-to-end ML workflows, including model training, evaluation, deployment, and monitoring.
  
• Analyze large, structured, and unstructured datasets to identify trends and business opportunities.
  
• Collaborate with product managers, software engineers, data engineers, and business stakeholders to define data-driven solutions.
  
• Optimize machine learning algorithms for performance, scalability, and reliability.
  
• Implement MLOps best practices, including CI/CD pipelines, model versioning, automated testing, and monitoring.
  
• Ensure data quality, governance, security, and compliance with organizational standards.
  
• Mentor junior data scientists and engineers through technical guidance and code reviews.
  
• Stay current with emerging AI, machine learning, and cloud technologies and recommend innovative solutions.
  

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
  
• 5–8+ years of experience in data science, machine learning, or AI engineering.
  
• Strong programming skills in Python (required); experience with SQL and one additional language (Java, Scala, or C++) is a plus.
  
• Experience with machine learning libraries such as scikit-learn, TensorFlow, PyTorch, or XGBoost.
  
• Strong understanding of statistics, predictive modeling, optimization, and feature engineering.
  
• Experience with data processing frameworks such as Spark or Hadoop.
  
• Proficiency in SQL and working with relational and NoSQL databases.
  
• Experience deploying machine learning models using cloud platforms (AWS, Azure, or Google Cloud).
  
• Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.
  
• Experience with Git, CI/CD, and DevOps practices.
  
• Excellent analytical, communication, and problem-solving skills.
  

Preferred Qualifications

• Experience with generative AI, large language models (LLMs), retrieval-augmented generation (RAG), or AI agents.
  
• Knowledge of MLOps tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML.
  
• Experience with streaming platforms such as Kafka.
  
• Familiarity with vector databases and semantic search.
  
• Cloud certifications or machine learning certifications.
  
• Experience leading technical projects or mentoring engineering teams.