Technical Data and Automation Analyst (Infrastructure and development)
Technical Data & Automation Analyst – Infrastructure & Development (Internship / Analyst Program)
Location: Remote
Work Format: Deliverable-based, flexible scheduling
Position Type: Internship / Analyst Program
Classification: Part-Time / Temporary / Seasonal
Program Duration: 8–12 weeks (aligned with academic term schedules and student availability)
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Role Overview
Morsby, Gorman, McCarthy LLC is seeking Technical Data & Automation Analyst Interns to support infrastructure and development initiatives through scalable data processing, automation, and systems development.
This role is designed to support the technical layer of a multi-disciplinary data workflow by enabling the efficient extraction, processing, structuring, and organization of large volumes of information. The primary focus of the position is to assist in developing and implementing technical solutions that improve the speed, consistency, and scalability of data handling across projects.
Participants will work with high-volume datasets and source materials, including research reports, institutional documents, policy papers, and other structured and unstructured data sources. The role involves working with tools and scripting approaches to automate repetitive processes, assist in parsing large documents, and support the transformation of raw data into structured outputs.
This position is part of a broader workflow that connects research, data structuring, systems development, and strategic analysis. The Technical Data & Automation Analyst serves as the technical bridge that enables efficient data flow across these functions.
The role is designed to provide hands-on exposure to applied data processing, scripting, and workflow automation within a real-world project environment.
The technical scope of this role is intentionally educational and introductory to intermediate in nature. Participants will not be expected to build production-level systems or enterprise-grade infrastructure, but rather to contribute to guided, scoped technical tasks that support learning and development.
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Core Purpose of the Role
The core purpose of this role is to support the technical processing and automation of data workflows by:
Assisting in the extraction of data from large and complex documents
Supporting the development of repeatable and scalable data processing workflows
Automating aspects of data cleaning, structuring, and organization
Improving efficiency in handling large volumes of information
Contributing to the creation of structured datasets from unstructured inputs
Supporting the integration of data into internal systems and workflows
This role is educational in nature and is intended to help participants develop practical experience in applied data processing, scripting, and automation.
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Key Responsibilities
Technical Data & Automation Analyst Interns may contribute to activities including, but not limited to:
Assisting in extracting data from large PDF files and document sets
Supporting the development of scripts to process and organize data
Working with structured and unstructured data sources
Automating repetitive data handling and transformation tasks
Cleaning, formatting, and standardizing data using technical tools
Supporting the creation of structured datasets from raw inputs
Assisting in developing workflows for handling high-volume data
Collaborating with Data & Systems Analysts to integrate automated outputs into structured datasets
Identifying inefficiencies in current workflows and proposing technical improvements
Supporting basic data parsing, text extraction, and pattern identification processes
Documenting scripts, workflows, and data processing methods where applicable
Depending on experience level, participants may take on more advanced automation or scripting tasks over time
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Example Project Applications
Participants may contribute to tasks such as:
Extracting structured data from large document sets
Automating formatting or cleaning of extracted data
Supporting workflows that process multiple reports into unified datasets
Assisting in organizing outputs for use by research and data teams
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Expected Deliverables
Participants may be expected to produce outputs such as:
Basic scripts for data extraction or processing
Automated workflows for handling repetitive data tasks
Cleaned and structured datasets generated through automated processes
Formatted outputs derived from raw document inputs
Documentation of scripts, logic, and workflow processes
Improved or optimized versions of existing data handling processes
Deliverables will be scoped based on project needs and participant experience level. All outputs will be reviewed to ensure quality, accuracy, and alignment with project objectives.
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Nature of the Work
This is a technically oriented internship role focused on applied data processing and workflow automation.
Participants will gain exposure to:
Working with large-scale document and dataset inputs
Understanding how automation can improve data workflows
Applying scripting or technical tools to real-world data challenges
Supporting scalable solutions for processing structured and unstructured information
Contributing to technical systems that support broader project functions
The role combines independent technical work with collaboration across research and data teams.
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Qualifications
Candidates for this role should ideally demonstrate:
Basic familiarity with programming or scripting concepts
Comfort working with structured data and technical tools
Strong problem-solving and analytical thinking ability
Attention to detail and accuracy in handling data
Ability to follow structured workflows and technical guidance
Willingness to learn and apply new tools or methods
Ability to work independently on assigned technical tasks
Advanced programming experience is not required. Foundational familiarity with programming concepts or coursework exposure is sufficient.
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Preferred Academic Backgrounds / Majors
This role may be particularly well suited to students from backgrounds such as:
Computer Science
Data Science
Information Systems
Software Engineering
Mathematics / Statistics
Engineering disciplines
Business Analytics (technical focus)
Related technical or quantitatively oriented fields
Candidates from adjacent disciplines with relevant technical skills are encouraged to apply.
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Nice to Have
The following are not required, but may strengthen a candidate’s fit:
Familiarity with Python or similar scripting languages
Exposure to data processing or automation workflows
Experience working with structured datasets
Basic understanding of handling large volumes of data
Exposure to text processing or data extraction tools
Familiarity with organizing or cleaning messy data
Interest in infrastructure, development, or large-scale projects
Exposure to tools or workflows used for parsing or processing documents
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Tools & Exposure
Participants may gain exposure to:
Python or similar scripting tools in a guided environment
Data processing workflows
Basic automation concepts
Structured data handling techniques
Document parsing and extraction approaches
Integration of automated outputs into structured systems
The role emphasizes practical application and learning rather than advanced software development.
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Preferred Candidate Level
This role is best suited for:
Junior and Senior undergraduate students
Graduate students
Strong Sophomore candidates with relevant technical exposure
Candidates should have at least introductory familiarity with technical or data-related coursework.
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Who This Role Is Best For
This role is a strong fit for:
Students interested in technical data work or automation
Individuals who enjoy solving problems through systems and tools
Candidates interested in scripting, data processing, or workflow optimization
Students seeking applied experience beyond coursework
Individuals interested in scalable solutions for handling large datasets
Candidates who are detail-oriented, logical, and technically curious
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Program Structure & Time Commitment
Program Duration
8–12 weeks aligned with academic schedules
Time Commitment
Approximately 5–15 hours per week (target ~10 hours/week)
Flexible scheduling to accommodate academic commitments
Extension Possibility
Extensions may be considered based on performance and project needs
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Compensation
This is an unpaid, educational internship designed for academic and professional development. The role focuses on skill-building, applied experience, and mentorship rather than paid employment.
This internship is structured as an educational experience and is intended to comply with applicable guidelines governing unpaid internships. The primary beneficiary of the program is the participant, with a focus on skill development, training, and academic alignment.
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Educational & Academic Credit Framework
This role is designed as a structured educational experience. Participants will receive defined technical tasks, mentorship, and guidance.
The position is intended to complement academic study and does not replace paid employee roles.
This internship may be eligible for academic credit depending on institutional requirements. Participants should coordinate with their university.
The organization is willing to provide documentation and supervision confirmation where appropriate.
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Learning Outcomes
Participants can expect to:
Develop practical experience with data processing and automation
Gain exposure to scripting and technical data workflows
Learn how to handle large-scale data inputs
Understand how automation supports real-world projects
Improve problem-solving and technical thinking skills
Gain experience working within a structured technical environment
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Supervision & Program Structure
Participants will operate within a defined supervisory structure with assigned oversight.
They may receive:
Defined technical assignments
Guidance on tools, scripting approaches, and workflow structure
Support when working with unfamiliar technical concepts
Feedback on outputs and processes
Ongoing coordination with project leads
Work will be reviewed to ensure quality, accuracy, and alignment with project standards.
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Feedback & Evaluation
Participants will receive feedback on:
Technical accuracy
Problem-solving approach
Efficiency and workflow improvements
Quality of outputs
Ability to follow and improve structured processes
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Professional Expectations
Participants are expected to:
Maintain accuracy and organization in technical work
Communicate clearly and professionally
Meet agreed-upon deadlines
Follow structured workflows and incorporate feedback
Demonstrate accountability and reliability
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What You’ll Gain
Exposure to real-world data processing challenges
Experience with automation and scripting concepts
Development of technical and analytical skills
Opportunity to contribute to scalable systems
Professional mentorship and feedback
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Growth Opportunities
High-performing participants may be considered for:
Advanced technical responsibilities
Extended roles
Future project involvement
Potential transition into longer-term technical positions
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Application Instructions
Apply via Handshake and submit:
Resume
Handshake profile
A brief 3–5 sentence statement of interest explaining your motivation and relevant technical experience
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Summary Positioning Statement
This role is intended to function as a structured, educational, technically oriented internship that provides hands-on experience in data processing, automation, and scalable workflow development. It is designed to support academic learning while providing practical exposure to real-world technical data challenges within infrastructure and development initiatives.