Note: The job is a remote job and is open to candidates in USA. SOSi is a leading technology and services integrator in the defense and government services industry. They are seeking a Senior Data Scientist to develop and sustain a scalable data ecosystem that enhances interoperability and mission-driven analytics for a DoD customer.
Responsibilities
- The contractor shall design and implement advanced ML models and statistical methods to optimize forecasting, risk assessment, and decision-making processes
- The contractor shall conduct data provenance tracking, ensuring documentation of sources, transformations, and lineage for compliance with governance policies
- The contractor shall submit the Data Provenance & Lineage Report, summarizing transformation workflows, feature engineering processes, and audit compliance
- 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
Skills
- 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
- Personnel must have demonstrated experience in building and validating AI/ML models using Python, TensorFlow, PyTorch, or Scikit-learn, integrating models into production environments, and optimizing performance for real-time analytics
- 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
- Possess the 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 is required
- Personnel must be able to translate operational challenges into analytic solutions, ensuring integration of structured, unstructured, and geospatial data
- Desirable but not required certifications include Google Professional Machine Learning Engineer, Microsoft Certified: Azure Data Scientist Associate, or TensorFlow Developer Certification
Benefits
- Full remote flexibility
Company Overview