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Affordability Analyst / Acquisition Data Scientist - Johns Hopkins University Applied Physics Laboratory
Data Scientist
Lead end‑to‑end data science for acquisition cost and schedule control, building pipelines, statistical models, and actionable dashboards to optimize resource allocation for DoD programs.
About the role
Key Responsibilities
- Design, develop, and maintain scalable data pipelines ingesting heterogeneous acquisition data from multiple sources.
- Apply statistical and machine learning techniques to model cost and schedule performance, identifying risk factors and improvement opportunities.
- Collaborate with program managers to translate analytical insights into actionable decision‑making tools and dashboards.
- Document data models, assumptions, and validation procedures to ensure reproducibility and compliance with DoD standards.
- Present findings to senior stakeholders, translating complex analyses into clear, concise recommendations.
Requirements
- Proven experience in Python, SQL, and data engineering for large datasets.
- Strong background in statistical modeling, predictive analytics, and machine learning.
- Hands‑on experience with data visualization tools (e.g., Tableau, Power BI) or equivalent.
- Excellent communication skills and ability to work cross‑functionally in a government‑contract environment.
- Knowledge of cloud platforms (AWS, Azure) and data governance best practices is a plus.
Skills
pythonsqlmachine learningdata analysis