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
Full remote flexibility.
Working at SOSi
All interested individuals will receive consideration and will not be discriminated against for any reason.