Job description

ACTIVE SECURITY CLEARANCE AT THE TS/SCI POLYGRAPH LEVEL IS REQUIRED We are seeking an innovative, analytical Data Scientist / Machine Learning Engineer to join our team in Annapolis Junction, MD, supporting advanced missile defense analytics and data modernization. In this role, you will pioneer artificial intelligence tools, machine learning models, and natural language processing (NLP) pipelines to triage, enrich, and mine massive, complex language datasets. You won't just run off-the-shelf algorithms—you’ll develop novel analytical tools and techniques designed for data mining, qualitative characterization of missile defense datasets, and mission-critical pattern recognition. If you thrive on training cutting-edge ML models, structuring unstructured data, and turning complex intelligence into decisive operational insights, you’ll fit right in with Team Nyla. The annual base salary range for this role is $119,000-$140,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things. • AI Tool Development & ML Modeling: Hands-on experience developing, training, evaluating, and deploying machine learning models using modern frameworks (e.g., PyTorch, TensorFlow, Scikit-learn). • Natural Language Processing (NLP): Proven background utilizing NLP methodologies for text classification, entity extraction, data triage, and parsing large language datasets. • Advanced Data Mining & Analysis: Demonstrated skill in designing custom algorithms, data mining techniques, and qualitative characterization routines for massive data sets. • Programming & Data Science Tools: Strong expertise in Python and standard data science libraries (Pandas, NumPy, SciPy) for analytics and data transformation pipelines. Education: Bachelor’s Degree in Data Science, Computer Science, Applied Mathematics, Machine Learning, or a related quantitative field, PLUS 7+ years of professional data science or ML engineering experience OR Master’s Degree in a related quantitative discipline, PLUS 5+ years of specialized experience in AI/ML development and analytics OR High School Diploma / GED , PLUS 11+ years of technical experience in data science, machine learning, and advanced analytics in lieu of a degree. Missile Defense & Threat Domain Knowledge: Experience analyzing defense telemetry, trajectory data, or performing qualitative characterization within missile defense mission areas. Large Language Models (LLMs): Experience fine-tuning, prompting, or deploying Large Language Models for automated summarization and triage pipelines. Cloud & Distributed Computing: Familiarity with training models or processing large datasets in cloud environments (AWS Sagemaker, EMR) or distributed platforms (Hadoop, Spark). Data Visualization: Proficiency with data visualization packages (Matplotlib, Seaborn, Plotly) or dashboards to present complex analytical metrics to stakeholders.

Requirements

Must-haves

ACTIVE SECURITY CLEARANCE AT THE TS/SCI POLYGRAPH LEVEL IS REQUIRED
AI Tool Development & ML Modeling: Hands-on experience developing, training, evaluating, and deploying machine learning models using modern frameworks (e.g., PyTorch, TensorFlow, Scikit-learn).
Natural Language Processing (NLP): Proven background utilizing NLP methodologies for text classification, entity extraction, data triage, and parsing large language datasets.
Advanced Data Mining & Analysis: Demonstrated skill in designing custom algorithms, data mining techniques, and qualitative characterization routines for massive data sets.
Programming & Data Science Tools: Strong expertise in Python and standard data science libraries (Pandas, NumPy, SciPy) for analytics and data transformation pipelines.
Missile Defense & Threat Domain Knowledge: Experience analyzing defense telemetry, trajectory data, or performing qualitative characterization within missile defense mission areas.
Large Language Models (LLMs): Experience fine-tuning, prompting, or deploying Large Language Models for automated summarization and triage pipelines.
Cloud & Distributed Computing: Familiarity with training models or processing large datasets in cloud environments (AWS Sagemaker, EMR) or distributed platforms (Hadoop, Spark).
Data Visualization: Proficiency with data visualization packages (Matplotlib, Seaborn, Plotly) or dashboards to present complex analytical metrics to stakeholders.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningmlaipythonaws

Platform: agile-ats
Effort: medium