Senior Earth Observation Data Scientist

 Published 14 days ago
 United States
Apply Now Please mention DailyRemote when applying

Disclaimer: Before you apply, please make sure the job is legit.

Attempting to apply for jobs might take you off this site to a different website not owned by us. Any consequence as a result for attempting to apply for jobs is strictly at your own risk and we assume no liability.


GAMA-1 Technologies seeks a highly motivated, customer-oriented remote Senior Earth Observation Data Scientist with AI/ML expertise to join our team. The successful candidate will have extensive applied experience using machine learning to analyze patterns within the National Oceanic and Atmospheric Administration’s (NOAA) Earth observation data, including metadata, ISO/UMM data standards, HDF5/ZARR data formats, and other science and/or environmental data formats. The ideal candidate will have a strong background in data analysis, with experience working in a software engineering or research environment. In this role, you will oversee data analysis from NOAA and NASA and develop data-driven analytic solutions using machine learning (ML) and artificial intelligence (AI).


This is a strategically important position that will work with multiple government teams across the agency to help lead scientific data analytics and help with the cross-functional execution of critical projects within the program. Responsibilities include advancing GAMA-1’s & NOAA’s use in digital transformation Artificial Intelligence (AI) and Machine Learning (ML) techniques, working with the enterprise stakeholders as they tackle data management, integration, dissemination, warehousing, and governance to manage the complexity of critical mission data for actionable insights and decision making. In this role, you should be highly analytical and knowledgeable in analysis, math, and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine learning and research.

 As a key Earth Observation Data Analyst within the company, it is required for the candidate to attend and play a strategic role in our bi-monthly and as-needed Digital Transformation and Data Management Center of Excellence (DT-DM CoE) in-house and customer-facing strategy, business development, and solutions working sessions. These working sessions are designed to drive digital, data-enabled IT and business transformation for our customers. The candidate will act as a Senior Data Analyst cross-functional and cross-organizational member of the DT-DM CoE group, which includes decision-makers and doers setting digital data transformation policy, guiding provider selection, and assisting with solution architecture and workload placement, with an eye on improving outcomes and managing risks. As well as working closely with business development to develop data stewardship and data analysis solutions for proposals and work assignments. As a member, you must incorporate innovative and best practices in data analytics, exploration leadership, and digital transformation culture insights that help solve complex problems and deliver data analytics modernization services to the group.

 Develop and implement comprehensive & innovative data analytics strategies to extract valuable insights to ensure NOAA can disseminate meaningful earth observation data to their customers, accelerating the speed and accuracy.

  • Oversee the analysis of earth observation data, ensuring that data is accurate, complete, and timely
  • Develop and maintain data analytic standards, policies, and procedures to ensure consistency across the organization
  • Manage data science activities, providing guidance and support on data analysis and modeling
  • Utilize machine learning and artificial intelligence techniques to develop predictive models, recommendation engines, and natural language processing (NLP) solutions
  • Utilize tools such as: AWS’ ML services such as Amazon SageMaker, Amazon Transcribe, Amazon Rekognition, Amazon Comprehend, and Amazon Lex to enhance and optimize data analysis
  • Work with stakeholders across the organization to identify data-driven opportunities for business growth and improvement
  • Ensure compliance with all relevant data privacy and security regulations
  • Monitor industry trends and provide recommendations for incorporating new technologies and methodologies into data management and analysis
  • Analyze collected data sources, extract critical information, and evaluate and monitor data quality to meet the organization's information system needs and requirements.
  • Apply specific functional knowledge, including working and general industry knowledge.
  • Develop or contribute solutions to various problems of moderate scope and complexity.
  • Work independently with some guidance and review or guide activities of more junior


  • PhD in Computer Science, Data Science, or extensive expertise and experience in the AI/ML field.
  • 5+ years of experience in data analysis, preferably earth observation science data.
  • Strong understanding of metadata and scientific data formats.
  • Experience conducting data analysis within cloud environments, explicitly working within AWS’ ML services.
  • Strong knowledge of data analysis tools such as Python, R, SQL to manipulate data and draw insights from large and small data sets
  • Demonstrated applied use cases with data visualization tools such as Tableau Tableau, D3.js, ggplot, or Bokeh
  • Experience working with data analysis concepts and activities, including industry best practices for data sourcing, key data elements, data quality management, metadata, and enterprise data management policy, process, and procedures
  • Experience facilitating information discovery sessions with business owners and other SMEs to extract requirements
  • Experience turning business requirements into technical requirements
  • Experience with working in Agile environments
  • Ability to work in a fast-paced environment with changes in priorities
  • Experience developing software code with object-oriented programing languages, including Java, C++, or C# Java and scripting languages, including Python, R, Bash, Batch, and PowerShell
  • Experience with implementing a variety of supervised and unsupervised machine learning techniques, including clustering, decision tree learning, and artificial neural networks
  • Knowledge of the real-world advantages and drawbacks of supervised and unsupervised machine learning
  • Knowledge of data standardization policies and standards sufficient to develop data management tools, including data dictionaries, data models, and metadata repositories
  • Possession of strong written communication skills in documentation, focused on accuracy, consistency, and standardized terminology
  • Government contracting experience is required
  • Ability to obtain and maintain a government security clearance

This is an exciting opportunity to work with cutting-edge technologies and make a significant impact in the field of data management and analysis. We encourage you to apply for this position if you are a passionate and innovative data leader with the required qualifications.


GAMA-1 is a rapidly growing technology business that is based in Greenbelt, Maryland. GAMA-1 Technologies provides strategic information assurance, information security, and business enterprise and networking solutions to the Federal Government. Our success is based on the utilization of industry and agency standards, establishment of standardized processes, and IT Services expertise. At GAMA-1, we believe employees should grow, achieve, and develop just as the company grows, achieves, and develops. GAMA-1 is committed to providing our employees with opportunities for career advancement throughout their employment. For more information, visit

GAMA-1 is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.

Ace Your Job Interview

Read our advice on how to answer the most common interview questions.