Data Scientist SME

We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We must not repeat job title. Must not include Job ID etc. Must preserve all substantive info. Remove boilerplate like cookie/navigation/legal/EEO etc. Also remove application instructions, duplicated lines. We need to parse the posting. Key sections: - Description: first paragraph(s) about role. Could be "About the role". We'll put that in

About the role

with

content. - Responsibilities: list of primary responsibilities bullet points. Use

• . - Requirements: maybe Basic Qualifications? Could be "Requirements". We'll include Basic Qualifications as Requirements. - Qualifications: maybe Preferred Qualifications as Qualifications. - Skills: maybe list of technical skills from Basic Qualifications (Python, etc.) Could be separate Skills section. But we need to avoid duplication. The instruction: "Prefer a few substantive sections over many thin ones." So we might combine some. However we need to follow headings list: we can include only those with real content. We could have About the role, Responsibilities, Requirements (Basic Qualifications), Qualifications (Preferred), Skills (maybe from Basic Qualifications), Benefits, Pay. Schedule not present (no schedule info). So omit Schedule. We must not create Pay/Schedule/Benefits unless posting actually states them. Pay is present: Pay Range $131,300.00 - $237,350.00. Benefits: there is a "Pay And Benefits" section describing benefits. So include Benefits. We must not include filler like "commensurate with experience". Not present. We need to preserve all substantive info: location, clearance, etc. Should we include location and clearance? They are not under headings but could be placed in About the role or a separate meta paragraph. The instruction: "Do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

  or drop it." So we can include location and clearance in a short

  maybe under About the role or separate meta paragraph. But we must not create a heading for them. So we can include a

  with location and clearance after About the role. We must not include boilerplate like "Leidos National Security Sector combines..." That's substantive? It describes the sector; maybe part of About the role. We'll keep. We must remove duplicated lines, cookie/navigation/legal/EEO etc. So remove the sections about Leidos, Pay And Benefits (but we need benefits), Securing Your Data, Commitment to Non-Discrimination, etc. Those are boilerplate/legal. Remove. Also remove the "If you're looking for comfort..." motivational fluff? That's maybe not substantive? It's fluff but could be considered boilerplate. Probably remove. Also remove "Original Posting September 16, 2026" etc. Remove. Also remove "#Chinook #NSBA" etc. Now craft HTML. Structure:

  About the role

  Turn complex data into mission advantage. Join Leidos on the Chinook Program supporting our Intelligence Community customer and play a critical role in transforming massive, complex datasets into actionable intelligence and mission insights. As a Data Scientist SME, you will bring advanced analytical expertise, innovative thinking, and technical leadership to a high performing Agile engineering team delivering next generation capabilities to our Intelligence Community customer. This is an opportunity to work at the intersection of data science, artificial intelligence, machine learning, cloud technology, and national security, where your expertise can directly influence how mission users understand data, identify patterns, and make critical decisions. You will serve as a technical authority while collaborating with software engineers, DevSecOps professionals, system architects, analysts, and mission stakeholders to solve challenging problems that don’t have off-the-shelf answers. If you are energized by applying advanced analytics to real-world mission challenges and want to see your work have a tangible impact, this is an opportunity to make a difference. Leidos National Security Sector combines technology-enabled services and mission software capabilities in the areas of cyber, logistics, security operations, and decision analytics to support our defense and intel customers’ mission to defend against evolving threats around the world. Our team’s focus is to ensure our customers have the right tools, technologies, and tactics to keep pace with an ever-evolving security landscape and succeed in their pursuit to protect people and critical assets.

  Then maybe a meta paragraph for location and clearance:

  Location: Primary work location: Gaithersburg, MD (also Alexandria, VA; Chantilly, VA; Aurora, CO; St. Louis, MO). Clearance: Active Top Secret/SCI clearance with ability to pass a Polygraph examination.

  Now Responsibilities:

  Responsibilities

  • Serve as the technical SME in data science and geospatial analytics, providing high-level guidance on complex technical problems related to the GEOINT mission.
  • Lead the design and development of sophisticated data science models and machine learning algorithms to analyze large, multi-source geospatial data sets (e.g., satellite imagery, sensor data, geospatial databases).
  • Apply deep knowledge of GEOINT, remote sensing, and spatial analysis to develop and implement solutions that enhance data-driven decision-making capabilities.
  • Provide strategic recommendations for leveraging new and emerging technologies, including machine learning, AI, and cloud platforms, to improve analytical workflows, efficiency, and mission outcomes.
  • Mentor and train junior data scientists and analysts, ensuring the application of best practices in data science and the development of mission-relevant expertise.
  • Work closely with GEOINT analysts, program managers, engineers, and other stakeholders to identify critical requirements, define technical approaches, and ensure that solutions align with mission objectives.
  • Conduct applied research to explore innovative data science techniques and emerging trends (e.g., deep learning, reinforcement learning, advanced geospatial algorithms) that can be applied to solve real-world intelligence problems.
  • Oversee the deployment and operationalization of data science models, ensuring they are scalable, reliable, and deliver actionable insights to GEOINT decision-makers.
  • Maintain high-quality documentation for models, methodologies, and analysis processes to support reproducibility, training, and knowledge transfer.
  Now Requirements (Basic Qualifications):

  Requirements

  • US citizenship is required per contract.
  • Bachelor’s degree in Data Science, Computer Science, Geospatial Science or related field and 12-15 years of prior relevant experience or Master’s with 10-13 years of prior relevant experience. May possess a Doctorate in technical domain.
  • 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, particularly in context of geospatial or remote sensing.
  • Deep knowledge of geospatial analytics tools (e.g., GIS, ArcGIS), remote sensing techniques, and the application of data science in the IC.
  • Expert proficiency in Python (or similar languages) and experience with data science libraries (Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, PyTorch, or equivalent technologies).
  • Strong experience with big data processing tools (e.g., Spark, PySpark, Kafka, Hadoop, AWS or Azure cloud platforms).
  • Expertise in working with geospatial data formats (e.g., GeoTIFF, Shapefiles, WMS, WFS) and spatial libraries (e.g., GeoPandas, Rasterio, GDAL).
  • Advanced experience in developing and operationalizing AI/ML models and algorithms for geospatial data (e.g., object detection from satellite imagery, spatial clustering, predictive analytics).
  • Strong background in data visualization and reporting tools (e.g., Tableau, PowerBI).
  • Strong leadership, communication, and collaboration skills, with the ability to work directly with senior government officials, analysts, and technical teams.
  • Excellent problem-solving and analytical skills with a demonstrated ability to translate technical challenges into actionable insights.
  Now Qualifications (Preferred Qualifications):

  Qualifications

  • Advanced certifications in data science or machine learning.
  • Familiarity with the customer’s mission and specific geospatial intelligence challenges.
  • Expertise in advanced deep learning techniques, particularly in computer vision and image analysis for geospatial applications.
  • Experience with cloud-native applications and distributed computing in a geospatial context.
  • Familiarity with satellite data analysis, and remote sensing models.
  • Published research or technical papers in geospatial intelligence, machine learning, or data science.
  Now Skills: Could be extracted from Requirements but we already have many skill items. To avoid duplication, maybe we don't need a separate Skills section. However the instruction says we can include Skills section if there is real specific content. We could create a Skills section summarizing technical skills: Python, libraries, big data tools, geospatial formats, visualization tools. But that would duplicate content from Requirements. The instruction: "Prefer a few substantive sections over many thin ones." So maybe we omit Skills and keep Requirements and Qualifications covering skills. However the headings list includes Skills; we can omit if not needed. It's okay to omit a heading if no real specific content beyond what's already covered. We'll omit Skills. Now Benefits: We have a section "Pay And Benefits" describing benefits: "Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. More details are available at www.leidos.com/careers/pay-benefits." We should include that as Benefits.

  Benefits

  Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. More details are available at www.leidos.com/careers/pay-benefits.

  Now Pay:

  Pay

  Pay Range $131,300.00 - $237,350.00. The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

  We should not include the boilerplate about "Pay And Benefits" duplicate; we already have Benefits separate. The Pay section includes the range and note. Now Schedule: not present, omit. We must not include any markdown code fences. Just output HTML. Check for any leftover boilerplate: we removed the "Leidos National Security Sector..." we kept in About the role. Good. Check for duplicated lines: we have not repeated. Check for any mention of "Original Posting September 16, 2026" etc removed. Check for "#Chinook #NSBA" removed. Check for "If you're looking for comfort..." removed. Check for "Step 10 is ancient history..." removed. Check for "For U.S. Positions: While subject to change..." removed. Check for "About Leidos" etc removed. Check for "Securing Your Data" etc removed. Check for "Commitment to Non-Discrimination" removed. Now ensure we didn't miss any substantive info: The description about role includes the mission, etc. We included location and clearance in About the role. We included location and clearance in a meta paragraph. We included responsibilities. We included requirements (basic qualifications). We included