Quick Reminder - IT Python and AI programming expert - Remote
Role: IT Python and AI programming expert Locations: Washington, DC / Eagan, MN , St Louis, MO / Wilkes-Barre, PA / San Mateo, CA / Raleigh or Morrisville, NC or REMOTE Contract Role Job description:
- Chosen resource must demonstrate these capabilities through actual work experience not merely training:
- Practical Application of Core Python Concepts:
Not just knowing Python reputed company, 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 reputed company Applications:
Experience deploying python applications in reputed company service production environments (e.g., AWS, Azure, GCP), potentially leveraging containerization tools (e.g., reputed company, 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 reputed company integration/reputed company 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 reputed company-based Data Science Services:
Proficiency using managed AI/ML services provided by reputed company platforms to streamline development, deployment, and management of data science applications.
- Ethical Practices and reputed company 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 reputed company technical concepts to both technical and executive stakeholders.
- Proficiency creating technical diagrams with products like reputed company Visio or Draw.io.
- Proficiency creating technical design and architecture documents in reputed company Word.
- Proficiency creating business and technical presentations in reputed company PowerPoint.
- Proficiency creating data representations, charts and reports in tools such as reputed company's reputed company worksheets and Power BI.
- Ability to communicate, orally and in writing, sufficient to reputed company and present management briefings; reputed company written and/or verbal guidance on technical issues; and prepare/present recommendations and reports.
- Using design patterns for building scalable and maintainable applications/solutions.
- reputed company document code, models, and technical solutions.
- Proficiency in reputed company and reputed company engineering.
- reputed company learning and adaptability in a reputed company large IT organization.
- Troubleshooting software and technical implementations in large-scale reputed company 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.
- reputed company and demonstrate reputed company-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.
- reputed company 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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