Data Scientist

🕒 July 1

🌲 Oregon – Remote

🌲 Oregon – Remote

💵 $67.4k - $139.9k / year

⏰ Full Time

🟠 Senior

🔴 Lead

📊 Data Scientist

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SOSi

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1989

📦 Logistics

💼 Consulting

🏥 Healthcare

Logistics • Consulting • Healthcare

SOSi is a government-focused defense and intelligence contractor that delivers mission-critical digital infrastructure, AI/ML, cyber, cloud, and intelligence services to the U. S. Army and other government agencies. The company provides solutions across software development, DevSecOps, ISR integration, data science, logistics, language and human services, training, and operations & maintenance to enable secure communications, advanced analytics, and operational effectiveness for U. S. and allied forces.

📋 Description

• Develop and refine predictive models. • Conduct exploratory data analysis. • Generate AI-driven insights to enhance intelligence and operational planning. • Integrate customer feedback into model iteration cycles, leveraging Agile development methodologies. • Submit Predictive Model Performance Report, documenting key findings, model accuracy metrics, and operational impact assessments. • Implement sprint-based Agile methodologies, ensuring rapid development cycles, backlog grooming, and alignment with mission requirements. • Conduct quarterly reviews to track cost efficiency, assess system performance, and optimize analytic workflows through the Quarterly Cost & Resource Utilization Report.

🎯 Requirements

• 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.