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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Science Engineer (With TS/SCI Clearance and a current Full Scope Poly) - **Company:** J&T Business Consulting - **Location:** Annapolis Junction, MD, United States - **Experience:** Expert - **Salary:** $245,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Automation of Tests, Microsoft Azure, C++ (Programming Language), Cloud Computing, Code Review, Computer Programming, Continuous Integration, DevOps, Apache Hadoop, Python (Programming Language), Machine Learning, NoSQL, Tensorflow, Azure Machine Learning, Search Technologies, SQL Databases, Google Cloud, Feature Engineering, Data Ingestion, Pytorch, Large Language Models, Apache Spark, Generative AI, Git, Scikit Learn, Kubernetes, Information Technology, Data Analytics, Xgboost, Integration Frameworks, Apache Kafka, Machine Learning Operations, Software Version Control, Data Pipelines, Software Library, Docker - **Published:** July 23, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=439377efddb3496b ## About the Role * 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., * 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. ## Description * 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. ## Related Videos - [Data Science, ML & AI in the Oil and Gas Industry at NDT Global - Dr. Katja Träumner](https://www.wearedevelopers.com/videos/1308-data-science-ml-ai-in-the-oil-and-gas-industry-at-ndt-global-dr-katja-traumner) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)