Data Scientist

Remote, OR, USA

Full-time

Clearance Requirement: None

Compensation: USD 67351 - USD 139882 - yearly

Company Description

Founded in 1989, SOSi is among the largest private, founder-owned technology and services integrators in the defense and government services industry. We deliver tailored solutions, tested leadership, and trusted results to enable national security missions worldwide.

Job Description

SOSi is seeking a Data Scientist to support mission requirements for a structured approach to further develop, integrate, and sustain a scalable, federated data ecosystem that enhances interoperability, governance, and mission-driven analytics for a DoD customer. The primary objective of the program is to bridge the operational gaps between DoD, IC, interagency, and non-traditional international partners to enable real-time information sharing, dynamic data integration, and mission-tailored analytical capabilities.

Essential Job Duties:

• The contractor shall develop and refine predictive models, conduct exploratory data analysis, and generate AI-driven insights to enhance intelligence and operational planning.

• The contractor shall integrate customer feedback into model iteration cycles, leveraging Agile development methodologies to maintain responsiveness to mission requirements.

• The contractor shall submit the Predictive Model Performance Report, documenting key findings, model accuracy metrics, and operational impact assessments.

• The contractor shall implement sprint-based Agile methodologies, ensuring rapid development cycles, backlog grooming, and alignment with mission requirements.

• The contractor shall provide a Rough Order of Magnitude (ROM) Estimate Report before each analytics project, detailing expected Full-Time Equivalent (FTE) hours, compute costs, storage consumption, and infrastructure requirements.

• The contractor shall conduct quarterly reviews to track cost efficiency, assess system performance, and optimize analytic workflows through the Quarterly Cost & Resource Utilization Report.

Qualifications

• Bachelor’s degree in Data Science, Statistics, Computer Science, or a related field, or;

• seven (7) years of equivalent experience in machine learning and predictive modeling.

• Proposed personnel possess the knowledge and capability to develop and refine predictive models, analyze large-scale datasets, and document analytic processes.

• Proficient in data mining, statistical modeling, and AI-driven forecasting techniques, with experience in working with structured and unstructured data sources.

• Knowledge of data visualization, feature selection, and geospatial analytics is required.

• Personnel must be capable of integrating data from multiple sources, ensuring model accuracy, and working within an Agile sprint cycle to deliver iterative improvements.

• Demonstrated experience in exploratory data analysis, feature engineering, and statistical testing. Experience with Python, R, SQL, and data science libraries (e.g., Pandas, NumPy, SciPy) is required.

• Personnel must have experience in cloud-based AI/ML tools, such as AWS SageMaker or Azure Machine Learning, and in implementing models into operational workflows.

Preferred Qualifications:

• Desirable but not required certifications include AWS Certified Data Analytics – Specialty, Microsoft Certified: Azure AI Fundamentals, or Certified Data Scientist (CDS).

Additional Information

Work Environment

• Full remote flexibility.

Working at SOSi

All interested individuals will receive consideration and will not be discriminated against for any reason.

SOSi is an equal employment opportunity employer and affirmative action employer. All interested individuals will receive consideration and will not be discriminated against on the basis of race, color, religion, sex, national origin, disability, age, sexual orientation, gender identity, genetic information, or protected veteran status. SOSi takes affirmative action in support of its policy to advance diversity and inclusion of individuals who are minorities, women, protected veterans, and individuals with disabilities.