Jobs via Dice
Leidos National Security Sector is seeking a Data Scientist Subject Matter Expert for the Chinook program, leading mission-critical projects that apply advanced data science techniques to national security challenges.
Position primarily based in Gaithersburg, MD but may be performed in Alexandria, VA; Chantilly, VA; Aurora, CO; or St. Louis, MO.
Clearance Level Required Top Secret with the ability to obtain SCI and a Polygraph.
Primary Responsibilities
Serve as the technical SME in data science and geospatial analytics, providing high-level guidance on complex technical problems.
Lead the design and development of sophisticated data science models and machine learning algorithms to analyze large, multi-source geospatial data sets.
Apply deep knowledge of GEOINT, remote sensing, and spatial analysis to develop and implement solutions that enhance data-driven decision‑making.
Provide strategic recommendations for leveraging emerging technologies, including AI, ML, and cloud platforms.
Mentor and train junior data scientists and analysts.
Work closely with GEOINT analysts, program managers, engineers, and stakeholders to define technical approaches and ensure alignment with mission objectives.
Conduct applied research to explore innovative data science techniques and emerging trends.
Oversee the deployment and operationalization of data science models, ensuring scalability, reliability, and actionable insights.
Maintain high‑quality documentation for models, methodologies, and analysis processes.
Basic Qualifications
Bachelor's degree in Data Science, Computer Science, Geospatial Science, or related field AND 12-15 years of relevant experience OR Master’s with 10-13 years of relevant experience. May possess a Doctorate.
10+ years of professional experience in data science.
5+ years of experience with GEOINT or geospatial data analysis.
Proven expertise in developing and implementing machine learning and AI models in geospatial context.
Deep knowledge of geospatial analytics tools (GIS, ArcGIS) and remote sensing techniques.
Expert proficiency in Python and data science libraries (TensorFlow, PyTorch, Pandas, NumPy).
Strong experience with big data processing tools (Spark, Hadoop, cloud platforms).
Expertise working with geospatial data formats and spatial libraries.
Advanced experience in operationalizing AI/ML models for geospatial data.
Strong background in data visualization and reporting tools.
Strong leadership, communication, and collaboration skills.
Excellent problem‑solving and analytical skills.
Preferred Qualifications
Advanced certifications in data science or machine learning.
Familiarity with customer mission and specific geospatial intelligence challenges.
Expertise in advanced deep learning techniques for geospatial applications.
Experience with cloud‑native applications and distributed computing in geospatial context.
Familiarity with satellite data analysis and remote sensing models.
Published research or technical papers in geospatial intelligence, machine learning, or data science.
#J-18808-Ljbffr
Position primarily based in Gaithersburg, MD but may be performed in Alexandria, VA; Chantilly, VA; Aurora, CO; or St. Louis, MO.
Clearance Level Required Top Secret with the ability to obtain SCI and a Polygraph.
Primary Responsibilities
Serve as the technical SME in data science and geospatial analytics, providing high-level guidance on complex technical problems.
Lead the design and development of sophisticated data science models and machine learning algorithms to analyze large, multi-source geospatial data sets.
Apply deep knowledge of GEOINT, remote sensing, and spatial analysis to develop and implement solutions that enhance data-driven decision‑making.
Provide strategic recommendations for leveraging emerging technologies, including AI, ML, and cloud platforms.
Mentor and train junior data scientists and analysts.
Work closely with GEOINT analysts, program managers, engineers, and stakeholders to define technical approaches and ensure alignment with mission objectives.
Conduct applied research to explore innovative data science techniques and emerging trends.
Oversee the deployment and operationalization of data science models, ensuring scalability, reliability, and actionable insights.
Maintain high‑quality documentation for models, methodologies, and analysis processes.
Basic Qualifications
Bachelor's degree in Data Science, Computer Science, Geospatial Science, or related field AND 12-15 years of relevant experience OR Master’s with 10-13 years of relevant experience. May possess a Doctorate.
10+ years of professional experience in data science.
5+ years of experience with GEOINT or geospatial data analysis.
Proven expertise in developing and implementing machine learning and AI models in geospatial context.
Deep knowledge of geospatial analytics tools (GIS, ArcGIS) and remote sensing techniques.
Expert proficiency in Python and data science libraries (TensorFlow, PyTorch, Pandas, NumPy).
Strong experience with big data processing tools (Spark, Hadoop, cloud platforms).
Expertise working with geospatial data formats and spatial libraries.
Advanced experience in operationalizing AI/ML models for geospatial data.
Strong background in data visualization and reporting tools.
Strong leadership, communication, and collaboration skills.
Excellent problem‑solving and analytical skills.
Preferred Qualifications
Advanced certifications in data science or machine learning.
Familiarity with customer mission and specific geospatial intelligence challenges.
Expertise in advanced deep learning techniques for geospatial applications.
Experience with cloud‑native applications and distributed computing in geospatial context.
Familiarity with satellite data analysis and remote sensing models.
Published research or technical papers in geospatial intelligence, machine learning, or data science.
#J-18808-Ljbffr