Senior Data Scientist

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SOSi

1001 - 5000 employees

Founded 1989

🏛️ Government

🤖 Artificial Intelligence

🔒 Cybersecurity

Government • Artificial Intelligence • Cybersecurity

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

• Design and implement advanced ML models and statistical methods to optimize forecasting, risk assessment, and decision-making processes. • Conduct data provenance tracking, ensuring documentation of sources, transformations, and lineage for compliance with governance policies. • Submit the Data Provenance & Lineage Report, summarizing transformation workflows, feature engineering processes, and audit compliance. • Implement sprint-based Agile methodologies, ensuring rapid development cycles, backlog grooming, and alignment with mission requirements. • 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. • Conduct quarterly reviews to track cost efficiency, assess system performance, and optimize analytic workflows through the Quarterly Cost & Resource Utilization Report.

🎯 Requirements

• Active TS/SCI Clearance. • Master’s degree in Data Science, Machine Learning, Statistics, or a related field, or; nine (9) years of equivalent experience in AI/ML model development and deployment. • Demonstrated experience in building and validating AI/ML models using Python, TensorFlow, PyTorch, or Scikit-learn. • Experience with Databricks, Apache Spark, or similar distributed data processing frameworks is required. • Experience working with geospatial datasets and integrating AI/ML solutions into mission-critical applications. • Knowledge and capability to develop advanced machine learning models and optimize analytic workflows for predictive and prescriptive intelligence. • Proficient in deep learning, supervised and unsupervised learning techniques, data wrangling, and feature engineering. • Experience with data provenance tracking, model explainability, and bias mitigation in AI/ML applications. • Ability to translate operational challenges into analytic solutions, ensuring integration of structured, unstructured, and geospatial data.

🏖️ Benefits

• Full remote flexibility.

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