Python and AI programming expert (SME)
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:
ā¢ 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.
ā¢ 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.
ā¢ 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).
ā¢ 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.
ā¢ 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.
ā¢ 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.
ā¢ 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.
ā¢ Chosen resource should exhibit through actual work experience not merely training:
ā¢ Desirable: hands on experience building MCP servers and integration with Agentic AI workflows.
ā¢ Communicating complex technical concepts to both technical and executive stakeholders.
ā¢ Proficiency creating technical diagrams with products like Microsoft Visio or Draw.io.
ā¢ Proficiency creating technical design and architecture documents in Microsoft Word.
ā¢ Proficiency creating business and technical presentations in Microsoft PowerPoint.
ā¢ Proficiency creating data representations, charts and reports in tools such as Microsoft s Excel worksheets and Power BI.
ā¢ 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.
ā¢ Using design patterns for building scalable and maintainable applications/solutions.
ā¢ Clearly document code, models, and technical solutions.
ā¢ Proficiency in Generative AI and prompt engineering.
ā¢ Continuous learning and adaptability in a very large IT organization.
ā¢ Troubleshooting software and technical implementations in large-scale enterprise ecosystems.
ā¢ API development and integration.
ā¢ Querying and managing data in both SQL and NoSQL databases.
ā¢ Tasks might include (neither exhaustive nor restrictive):
ā¢ Data science tasks such as data acquisition, data cleaning, and feature extraction.
ā¢ Develop and demonstrate proof-of-concepts (PoC); independently or in a team.
ā¢ Create technical diagrams and documentation to show PoC implementations and potential production implementation.
ā¢ Researching and presenting to teammates on the latest tools/packages/capabilities being developed.
ā¢ Make recommendations on relevant tools/packages to use for production environments.
ā¢ Work with relevant governance committees to document and obtain approval for exploratory data science efforts.
ā¢ Consulting with members of architecture teams to identify potential automation solutions which may include AI/ML.
ā¢ Collaborating with cross functional teams on holistic AI/ML solutions.
Apply Now
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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:
ā¢ 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.
ā¢ 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.
ā¢ 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).
ā¢ 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.
ā¢ 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.
ā¢ 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.
ā¢ 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.
ā¢ Chosen resource should exhibit through actual work experience not merely training:
ā¢ Desirable: hands on experience building MCP servers and integration with Agentic AI workflows.
ā¢ Communicating complex technical concepts to both technical and executive stakeholders.
ā¢ Proficiency creating technical diagrams with products like Microsoft Visio or Draw.io.
ā¢ Proficiency creating technical design and architecture documents in Microsoft Word.
ā¢ Proficiency creating business and technical presentations in Microsoft PowerPoint.
ā¢ Proficiency creating data representations, charts and reports in tools such as Microsoft s Excel worksheets and Power BI.
ā¢ 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.
ā¢ Using design patterns for building scalable and maintainable applications/solutions.
ā¢ Clearly document code, models, and technical solutions.
ā¢ Proficiency in Generative AI and prompt engineering.
ā¢ Continuous learning and adaptability in a very large IT organization.
ā¢ Troubleshooting software and technical implementations in large-scale enterprise ecosystems.
ā¢ API development and integration.
ā¢ Querying and managing data in both SQL and NoSQL databases.
ā¢ Tasks might include (neither exhaustive nor restrictive):
ā¢ Data science tasks such as data acquisition, data cleaning, and feature extraction.
ā¢ Develop and demonstrate proof-of-concepts (PoC); independently or in a team.
ā¢ Create technical diagrams and documentation to show PoC implementations and potential production implementation.
ā¢ Researching and presenting to teammates on the latest tools/packages/capabilities being developed.
ā¢ Make recommendations on relevant tools/packages to use for production environments.
ā¢ Work with relevant governance committees to document and obtain approval for exploratory data science efforts.
ā¢ Consulting with members of architecture teams to identify potential automation solutions which may include AI/ML.
ā¢ Collaborating with cross functional teams on holistic AI/ML solutions.
Apply Now
Apply Now