Senior Data Scientist, Secret Clearance

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

📋 Description

• Develop, test, and communicate alternative statistical frameworks.

• Implement thorough experimental design, hypothesis testing, and statistical analysis on extensive federal datasets, ensuring results meet stringent requirements and security standards.

• Create, construct, and launch end-to-end machine learning pipelines (including predictive modeling, anomaly detection, and NLP), synchronizing model development life cycles with the Agile SAFe v6.0 roadmap.

• Write scripts and frameworks to modernize legacy analytics systems into highly distributed, cloud-native processing and intelligence solutions specifically tailored for AWS GovCloud.

• Establish standardized methods for data extraction, manipulation, and feature engineering across enterprise-level relational and non-relational datastores.

• Collaborate with data engineers to design and incorporate ML models directly into high-volume, low-latency batch and stream processing pipelines (e.g., Kafka, Spark) that seamlessly connect application and analytics layers.

• Act as the primary data science advisor throughout the entire program.

• Collaborate with software engineers, data architects, and customer application specialists to assess technical trade-offs and enhance advanced analytics capabilities.

• Utilize Jira, Confluence, and SAFe processes to convert high-level mission capabilities and agency mandates into foundational analytical epics, technical features, and modeling roadmaps.

⛳️ Requirements

• An active U.S. Secret clearance is mandatory.

• U.S. Citizenship is required to comply with federal contract mandates.

• A Bachelor’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field with 10–12 years of relevant data science and machine learning experience OR a Master’s degree in a related field with 8–10 years of relevant experience OR a PhD in a related field with 5–7 years of relevant experience.

• Profound expertise in advanced statistical methods (regression analysis, forecasting, causal inference) and machine learning algorithms (supervised/unsupervised learning, ensemble methods, deep learning, NLP).

• Proficiency in Python (including the PyData stack: Pandas, NumPy, Scikit-Learn, SciPy) and advanced SQL (complex joins, window functions, analytical queries) for managing multi-million row datasets.

• Extensive experience in designing and deploying scalable ML models and analytics pipelines within AWS and AWS GovCloud, particularly using SageMaker, Redshift, Glue, EMR, Athena, S3, and DynamoDB.

• Advanced knowledge of extracting and manipulating data from enterprise-grade relational databases (Oracle, PostgreSQL), NoSQL engines, and massive parallel processing (MPP) data warehouses.

• High proficiency with Git, Jira, Confluence, and MLOps principles in an automated DevSecOps environment for managing model versioning and deployment pipelines.

• Demonstrated ability to work independently on highly complex, mission-critical projects, exercising considerable discretion in judgment.

• Strong interpersonal skills with the capability to convey complex mathematical and analytical concepts to both engineering teams and senior federal stakeholders.

🏝️ Benefits

• Highly competitive salary based on qualifications and experience.

• Comprehensive company-paid healthcare for you (we cover your premiums and deductibles).

• 401(k) plan with company matching.

• Travel and performance incentives.

• Three weeks of paid time off (in addition to Federal Holidays).

• $5,000 annual training allowance.