Develop and maintain Python-based data pipelines that collect, process, and ingest data from multiple sources.
Improve existing data workflows with a focus on quality assurance, sustainability, documentation, and maintainability.
Ensure analytic workflows are reproducible, well-structured, and scalable.
Support responsible handling of sensitive data in compliance with FERPA and AACOM data governance standards.
Develop dashboards and data visualization tools primarily using Tableau and Python.
Maintain and enhance existing dashboards, internal analytics tools, and client-facing data products.
Translate complex datasets into accessible and actionable visual insights.
Translate defined research designs into executable analytic workflows.
Clean, transform, and validate complex administrative and survey datasets.
Conduct quantitative analyses with increasing independence over time.
Contribute to applied research initiatives including workforce studies, survey analysis, and text-based or NLP projects.
Support the development and operationalization of statistical and/or ML models used in research and operational initiatives.
Partner with colleagues across AACOM departments to support strategic data and analytics initiatives.
Contribute to a culture of innovation, continuous learning, and process improvement.
Document workflows, methodologies, and technical processes clearly and consistently.
Stay current on emerging tools, technologies, and best practices in data science and analytics.

Bachelor’s degree in Data Science, Statistics, Computer Science, Public Health, or a related field; or equivalent professional experience.
Three(3) or more years of experience working with Python and SQL.
One(1)or more years of experience building data models and using advanced analytics, including machine learning or statistical modeling techniques.
Strong proficiency in Python and SQL.
Experience with data manipulation, statistical analysis, machine learning, and data visualization libraries.
Strong data cleaning, validation, and troubleshooting skills.
Experience working with structured datasets and relational databases.
Exposure to cloud platforms such as AWS and/or Azure.
Understanding of Dev Ops or deployment practices.
Comfort using modern AI-assisted tools where appropriate.
Ability to work independently, manage ambiguity, and solve problems proactively.
Strong attention to detail and documentation practices.
Intellectual curiosity, adaptability, and openness to feedback.
Ability to manage sensitive data responsibly and in compliance with FERPA.

Data Scientist

Key skills