TS SCI Cleared Data Scientist - Sr

Nalley Consulting•Charlottesville, VA

1d•Onsite

About The Position

Nalley Consulting is hiring a Senior Data Scientist to support mission-driven projects in Charlottesville, Virginia. This role combines data science and data engineering, using expertise to build advanced technology solutions and lead data engineering activities. The position oversees the development and deployment of pipelines and platforms that organize disparate data and make it meaningful. It also mentors a multidisciplinary team of analysts, data engineers, developers, and data consumers in a fast-paced, agile environment, and oversees the assessment, design, development, and maintenance of scalable client platforms. Raw coding experience without AI-assisted IDEs is required.

Requirements

TS/SCI U.S. government security clearance and CI polygraph; current CI polygraph conducted within the past seven years is highly prioritized.
Bachelor's degree or equivalent experience.
CompTIA Security+ certification.
At least 3 years of experience designing, developing, operationalizing, and maintaining complex data applications.
At least 3 years of raw coding experience with Python or Java and PostgreSQL or similar databases.
At least 3 years of experience developing code for data manipulation, data analysis, or data modeling.
Experience creating and integrating code to retrieve, parse, and process data across multiple systems or applications.
Experience developing scripts and programs to convert different types of data into usable formats and supporting teams to scale, monitor, and operate data platforms for mission goals.
Experience developing algorithms using Python and SQL.
Experience with Python data science and visualization packages.
Experience leading development of solutions to complex problems.
Experience working in a TS environment with onsite development tools.
Experience with database administration or data analytics.
Experience with structured and unstructured data.
Raw coding experience without AI-assisted IDEs.

Nice To Haves

12 or more years of experience in Extract, Transform, and Load (ETL) processes.
7 or more years of experience designing, developing, operationalizing, and maintaining complex data applications.
7 or more years of raw coding experience with Python or Java and PostgreSQL or similar databases.
7 or more years of experience developing code for data manipulation, data analysis, or data modeling.
At least 3 years of experience implementing and developing AI and machine learning.
Experience with DevSecOps tools, including GitHub.
Experience working within the Intelligence Community.
Experience with a cloud environment, including AWS, Microsoft Azure, or Google Cloud.
Experience with Streamlit or Tkinter.
Experience with Agile software development.

Responsibilities

Conduct data analytics, data engineering, data mining, exploratory analysis, predictive analysis, and statistical analysis; correlate data using scientific techniques and produce graphical, written, visual, and verbal products to support analytic decisions.
Retrieve information from varied sources and analyze datasets; build AI tools that automate processes, including machine-learning tools such as recommendation engines or automated lead-scoring systems.
Perform statistical analysis, apply data-mining techniques, and build prediction systems.
Use data visualization and graphical applications, including Microsoft Office Power BI and Tableau; use data science languages such as R and Python; manage and merge disparate data sources, preferably with Python or SQL; and apply statistical analysis and data-mining algorithms.
Use experience with large-data Multi-INT analytics, machine learning, and automated predictive analytics.
Lead data engineering activities, including development and deployment of pipelines and platforms that organize disparate data.
Mentor analysts, data engineers, developers, and data consumers.
Assess, design, build, and maintain scalable client platforms.
Develop, integrate, and maintain code and scripts for retrieving, parsing, processing, manipulating, analyzing, modeling, and converting data across systems into usable formats.
Support project teams in scaling, monitoring, and operating data platforms in support of mission goals.
Lead development of solutions to complex problems.