Data Scientist - Transform Mission Data with Analytics

OPS Consulting, LLC; Augusta (GA); On-site; USD 50,000 - 290,000; Full time

Benefits offered by this job

Healthcare benefits

Retirement plan

Paid time off and education benefits

Job summary

Swift is seeking a Data Scientist for a role in Augusta, GA to extract insights from large datasets and support mission needs. The ideal candidate blends mathematical, statistical, computational, and domain expertise to analyze data, develop models, and communicate findings to technical and non-technical stakeholders.

The role emphasizes building reproducible analytics workflows with Python, Jupyter notebooks, and Pandas, plus integrating data from multiple sources via APIs.

Qualifications

• Bachelor's degree or equivalent experience in a quantitative field.
• Minimum of three years of data analysis or data science experience.
• Experience with data compilation and integration from multiple sources using scripting and APIs.
• Experience applying statistical analysis and data modeling techniques.
• Proficiency in Python for data analysis including Jupyter notebooks and Pandas.
• Experience developing rapid analytic prototypes and performance metrics.

Responsibilities

• Apply core data science skills to extract actionable insights from large datasets.
• Compile and manage data from multiple sources using scripting and APIs.
• Develop statistical analyses, data models, and quantitative methods to characterize datasets.
• Build rapid analytic prototypes to generate metrics and insights for mission needs.
• Develop reproducible data workflows using Python and common data science tools.
• Interact with APIs and existing tools to retrieve, process, and analyze data.

Skills

Python

Jupyter notebooks

Pandas

Data analysis

APIs

Data modeling

Education

Bachelor's degree in Mathematics/Statistics/CS/Data Science

Tools

SQL

Job description

Swift is seeking a Data Scientist for a role in Augusta, GA to extract insights from large datasets and support mission needs. The ideal candidate blends mathematical, statistical, computational, and domain expertise to analyze data, develop models, and communicate findings to technical and non-technical stakeholders.

The role emphasizes building reproducible analytics workflows with Python, Jupyter notebooks, and Pandas, plus integrating data from multiple sources via APIs.