Senior Data Scientist

This is a fully remote position, open to applicants in Oregon.

📋 Description

• Develop and execute sophisticated machine learning models and statistical techniques aimed at enhancing forecasting, risk assessment, and decision-making processes.

• Perform data provenance tracking, ensuring the documentation of sources, transformations, and lineage to comply with governance policies.

• Prepare and submit the Data Provenance & Lineage Report, which summarizes transformation workflows, feature engineering processes, and audit compliance.

• Apply sprint-based Agile methodologies to guarantee rapid development cycles, effective backlog grooming, and alignment with mission objectives.

• Generate a Rough Order of Magnitude (ROM) Estimate Report prior to each analytics project, outlining anticipated Full-Time Equivalent (FTE) hours, compute costs, storage requirements, and infrastructure needs.

• Conduct quarterly evaluations to monitor cost efficiency, assess system performance, and optimize analytic workflows through the Quarterly Cost & Resource Utilization Report.

⛳️ Requirements

• Possession of an active TS/SCI Clearance.

• A Master’s degree in Data Science, Machine Learning, Statistics, or a related discipline, or a minimum of nine (9) years of comparable experience in AI/ML model development and deployment.

• Proven experience in constructing and validating AI/ML models utilizing Python, TensorFlow, PyTorch, or Scikit-learn.

• Familiarity with Databricks, Apache Spark, or similar distributed data processing frameworks is essential.

• Experience with geospatial datasets and the integration of AI/ML solutions into mission-critical applications.

• Expertise in developing advanced machine learning models and optimizing analytic workflows for predictive and prescriptive intelligence.

• Proficient in deep learning, both supervised and unsupervised learning techniques, data wrangling, and feature engineering.

• Experience with data provenance tracking, model explainability, and bias mitigation in AI/ML applications.

• Capacity to translate operational challenges into analytic solutions, ensuring the integration of structured, unstructured, and geospatial data.

🏝️ Benefits

• Complete remote flexibility.