Job Description
Role: IT Python and AI programming expert
Location: Washington DC, Eagan MN, St Louis MO, Wilkes-Barre PA, San Mateo CA, Raleigh or Morrisville NC, or Remote
Duration: 12 months
Client: IPS/USPS
Note: candidates meet the residency requirements (Last 5 years in the US with no more than 6 months out of the country).
- List of tasks to be performed:
- Practical Application of Core Python Concepts: Not just knowing Python syntax, but demonstrating a track record of building and deploying Python applications or scripts that address IT operational needs, automate processes, or handle data management.
- Data Engineering and Analysis Skills: Demonstrable experience with data acquisition, cleaning, preprocessing, and transformation using Python tools and techniques for building robust analysis on large scale data sets.
- Implementing and Deploying Cloud Applications: Experience deploying python applications in cloud service production environments (e.g., AWS, Azure, Google Cloud Platform), potentially leveraging containerization tools (e.g., Docker, Kubernetes).
- Understanding of Software Engineering Best Practices: Experience in applying principles like version control (Git), writing clear and testable code, participating in code reviews, and using continuous integration/continuous deployment (CI/CD) pipelines.
- Knowledge of Data Science Best Practices: Demonstrated understanding and implementation of data science solutions such as data pipelining, feature engineering, or creation of Machine Learning Models.
- Familiarity with Cloud-based Data Science Services: Proficiency using managed AI/ML services provided by cloud platforms to streamline development, deployment, and management of data science applications.
- Ethical Practices and Security Knowledge: A demonstrated awareness and application of ethical guidelines for data science solutioning, including addressing bias, ensuring data privacy, and implementing secure coding practices in Python-based solutions.
- Chosen resource should exhibit through actual work experience not merely training:
- Desirable: hands on experience building MCP servers and integration with Agentic AI workflows.
- Communicating complex technical concepts to both technical and executive stakeholders.
- Proficiency creating technical diagrams with products like Microsoft Visio or Draw.io.
- Proficiency creating technical design and architecture documents in Microsoft Word.
- Proficiency creating business and technical presentations in Microsoft PowerPoint.
- Proficiency creating data representations, charts and reports in tools such as Microsoft s Excel worksheets and Power BI.
- Ability to communicate, orally and in writing, sufficient to develop and present management briefings; provide written and/or verbal guidance on technical issues; and prepare/present recommendations and reports.
- Using design patterns for building scalable and maintainable applications/solutions.
- Clearly document code, models, and technical solutions.
- Proficiency in Generative AI and prompt engineering.
- Continuous learning and adaptability in a very large IT organization.
- Troubleshooting software and technical implementations in large-scale enterprise ecosystems.
- API development and integration.
- Querying and managing data in both SQL and NoSQL databases.
- Tasks might include (neither exhaustive nor restrictive):
- Data science tasks such as data acquisition, data cleaning, and feature extraction.
- Develop and demonstrate proof-of-concepts (PoC); independently or in a team.
- Create technical diagrams and documentation to show PoC implementations and potential production implementation.
- Researching and presenting to teammates on the latest tools/packages/capabilities being developed.
- Make recommendations on relevant tools/packages to use for production environments.
- Work with relevant governance committees to document and obtain approval for exploratory data science efforts.
- Consulting with members of architecture teams to identify potential automation solutions which may include AI/ML.
- Collaborating with cross functional teams on holistic AI/ML solutions.
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