Data Scientist

SOSi sosi.com Open · verified Oct 24, 2026

Remote United States Full-time Mid-level Data Science

At a glance

Mid-level Data Science role at SOSi. Remote, United States · full-time · $67,351–$139,882 base.

SalaryStated by SOSi

$67,351 – $139,882

Base salary for this role, in USD per year, as published in the posting.

RoleData Science

SeniorityMid-level

LocationUnited States

WorkplaceRemote

EmploymentFull-time

Base pay$67,351–$139,882

PostedJun 30, 2026 · 3mo ago

Role brief

remoteroles summary, based on the employer's posting.

What you'll do

Develop predictive models, examine data, and produce AI-based findings to support intelligence and operational planning
Revise models using customer feedback, working in Agile sprints to keep delivery responsive to mission needs
Record model findings, accuracy measures, and operational effects in a performance report
Before each analytics project, estimate staffing, computing, storage, and infrastructure needs; review costs and system performance quarterly

What you bring

A degree in data science, statistics, computer science or a related area, or seven years of equivalent machine learning and predictive modeling work
Experience analyzing large datasets from structured and unstructured sources, including feature engineering and statistical testing
Use Python, R, SQL, data science libraries, and cloud AI/ML platforms such as SageMaker or Azure Machine Learning
Knowledge of data visualization, feature selection, geospatial analytics, and deploying models in operational workflows

Who this fits

This fully remote role suits a data scientist who can deliver predictive analytics in Agile sprint cycles and document model performance and resource use. You need a relevant degree or the stated equivalent experience. The listed certifications are optional.

From the employer

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.

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.

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).

Work Environment