Senior API Integration Engineer

Nyla Technology Solutions•Annapolis Junction, MD

About The Position

We are seeking a versatile, driven Data Scientist / AI/ML Automation Engineer to transform raw collection streams into automated, high-value intelligence. In this key role, you will apply Python data science toolkits, RESTful APIs, and machine learning techniques to optimize collection processing, automate analytical workflows, and extract actionable insights from high-volume data flows. Whether you are already experienced in AI/ML or a strong Data Scientist eager to expand your skillset through sponsored advanced coursework, you will play a hands-on role in constructing API data retrieval tools, structuring complex dataframes, and developing dynamic analytical capabilities.

Requirements

Mastery of Python for complex data manipulation, dataframe structuring (e.g., pandas), and data aggregation.
Strong proficiency interacting with, reading, consuming, and building tools to retrieve data via RESTful APIs.
Practical experience applying algorithmic logic or AI/ML techniques to automate data ingestion, collection processing, and workflow optimization.
Background or experience working directly with SIGINT data collection, dataflow mechanics, or intelligence data processing systems.
Demonstrated ability to translate raw, multi-source dataset feeds into structured analytical pipelines.
Bachelor’s Degree in Data Science, Computer Science, Computational Linguistics, Mathematics, or a related technical discipline, PLUS 10 + years of professional experience in data science, NLP, or software engineering OR Associate's Degree PLUS 12+ years of specialized technical experience in lieu of a degree.
ACTIVE SECURITY CLEARANCE AT THE TS/SCI POLYGRAPH LEVEL IS REQUIRED

Nice To Haves

Experience crafting custom data visualizations using Plotly, Shapely, GeoPandas, or interactive mapping libraries.
Operational familiarity or proficiency with XKEYSCORE (XKS) / DX tools and complex SIGINT dataflow architectures.
Hands-on experience with Splunk, Elastic, Kibana (ELK stack), SQL databases, or enterprise networking concepts.
Exposure to front-end UI framework scripting using Bootstrap (HTML) or Pyodide.

Responsibilities

Apply Python data science toolkits, RESTful APIs, and machine learning techniques to optimize collection processing.
Automate analytical workflows.
Extract actionable insights from high-volume data flows.
Construct API data retrieval tools.
Structure complex dataframes.
Develop dynamic analytical capabilities.