Data and Systems Analyst Intern (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 Data & Systems Analyst Interns to support infrastructure and development initiatives through structured data organization, dataset development, information processing, and systems support.
This role is part of a broader multi-disciplinary infrastructure program and is designed to support how information is structured, organized, and utilized across project workflows. The purpose of the role is to transform large volumes of unstructured or semi-structured information into clean, organized, and usable data formats that support analysis, planning, and execution.
Participants will work with a wide range of materials, including research outputs, institutional reports, policy documents, sector data, and internally generated materials. The work produced through this role will contribute to internal data systems, structured datasets, and organized information frameworks used across research, strategy, communications, and business development functions.
The Data & Systems Analyst position is designed to provide applied, hands-on experience in real-world data handling, organization, and systems thinking within a project-based environment.
This role functions as a foundational data and systems layer within a multi-disciplinary team structure. Data & Systems Analysts help ensure that information collected across projects is structured, usable, and accessible for downstream analysis and decision-making.
Participants will work under structured guidance with defined deliverables, regular feedback, and mentorship throughout the program. This role is aligned with academic learning objectives and is intended to complement coursework in data, analytics, business, economics, or related fields.
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Core Purpose of the Role
The core purpose of this role is to support the data organization and systems development needs of infrastructure and development projects by:
Transforming unstructured information into structured datasets
Supporting the development of organized data systems and workflows
Ensuring consistency, accuracy, and usability of project data
Assisting in the creation of structured inputs for research, strategy, and reporting functions
Contributing to a multi-disciplinary workflow that connects research, data, strategy, communications, and implementation planning
This role is educational in nature and designed to help participants strengthen their ability to work with real-world data, build structured outputs, and understand how data supports broader project execution.
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Key Responsibilities
Data & Systems Analyst Interns may contribute to a range of activities, including but not limited to the following:
Extract structured data from reports, PDFs, and research materials
Build and maintain datasets using Excel or Google Sheets
Organize, label, and categorize information for internal use
Clean, standardize, and validate data to ensure consistency and accuracy
Support the development of internal data tracking systems and organizational frameworks
Translate unstructured or loosely structured information into clear, usable formats
Assist in maintaining organized repositories of structured data and project materials
Support research teams by preparing structured data inputs for analysis and reporting
Identify patterns, inconsistencies, and gaps within datasets
Contribute to improving internal workflows related to data organization and accessibility
Assist in documenting data structures, definitions, and organizational logic where applicable
Depending on project needs and candidate strengths, participants may take on more advanced data structuring responsibilities over time
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Expected Deliverables
Participants may be expected to produce structured outputs such as:
Organized datasets in Excel or Google Sheets
Cleaned and standardized data tables
Categorized and labeled data repositories
Structured data extraction sheets from reports or documents
Internal data tracking and organization templates
Documentation of data structures, definitions, and organization logic
Deliverables will be clearly defined and scoped based on project needs and participant experience level. Work will be reviewed to ensure quality, consistency, and alignment with project objectives.
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Nature of the Work
This is a structured, data-focused internship role designed to provide practical exposure to how information is processed and structured in real-world project environments.
The role goes beyond basic data entry. Participants will gain exposure to applied data workflows, including:
Working with real-world institutional and project data
Understanding how data quality affects analysis and decision-making
Learning how raw information is converted into structured datasets
Supporting the creation of internal systems that enable efficient data use
Contributing to a collaborative environment in which data supports research, strategy, and execution functions
Work may involve both independent assignments and collaboration with team members, depending on task type and project phase.
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Qualifications
Candidates for this role should ideally demonstrate the following:
Strong attention to detail and organizational ability
Comfort working with structured data and spreadsheets
Ability to process large volumes of information accurately
Analytical mindset and problem-solving capability
Ability to follow structured workflows and guidelines
Strong time management and reliability
Ability to work independently while maintaining consistency in outputs
Willingness to learn and adapt within a multi-disciplinary team environment
Prior formal experience is not required if the candidate demonstrates strong analytical or organizational ability.
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Preferred Academic Backgrounds / Majors
This role may be particularly well suited to students or early-career individuals from backgrounds such as:
Data Analytics
Business Analytics
Information Systems
Economics
Finance
Mathematics / Statistics
Operations / Supply Chain
Engineering (non-specialized)
Related analytical or quantitatively oriented disciplines
Candidates from adjacent fields with strong data-handling ability are encouraged to apply.
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Nice to Have
The following are not required, but may strengthen a candidate’s fit:
Experience working with Excel or Google Sheets beyond basic usage
Exposure to data cleaning, formatting, or organization
Coursework in data analytics, business analytics, or quantitative methods
Experience working with structured datasets
Familiarity with organizing large sets of information
Interest in infrastructure, development, or project-based work
Exposure to tools or workflows used to process or organize large volumes of information
Familiarity with structured documentation or knowledge management tools (e.g., Notion or similar platforms)
Basic familiarity with scripting, automation, or tools used for data processing (e.g., Python or similar) is helpful but not required
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Tools & Exposure
Participants may gain exposure to:
Microsoft Excel
Google Sheets
Structured data workflows
Internal data organization systems
Documentation and knowledge management tools (e.g., Notion or similar platforms)
Introductory exposure to tools or concepts used in data processing or automation environments
No advanced programming or technical background is required for this role.
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Preferred Candidate Level
This role is designed to be accessible to strong candidates across multiple academic stages:
Sophomore and Junior students preferred
Junior, Senior, and Graduate students may take on more advanced responsibilities
Exceptional Freshman candidates may be considered based on demonstrated ability
Strong candidates at any level are encouraged to apply
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Who This Role Is Best For
This role is a strong fit for:
Students interested in data organization, analytics, or systems work
Individuals who enjoy working with structured information
Candidates who prefer organization, accuracy, and system-building tasks
Students seeking applied, hands-on experience beyond coursework
Individuals interested in how data supports real-world projects
Candidates who are detail-oriented, methodical, and process-driven
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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 responsibilities
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 guidance, defined responsibilities, and mentorship throughout the program.
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 are responsible for coordinating 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 data organization and structuring skills
Strengthen proficiency in Excel and data handling
Learn how to clean, standardize, and validate real-world data
Gain experience converting unstructured information into structured datasets
Understand how data supports research, strategy, and decision-making
Improve attention to detail and analytical thinking
Gain exposure to infrastructure and development project workflows
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Supervision & Program Structure
Participants will operate within a defined supervisory structure, with clearly assigned points of contact and oversight.
They may receive:
Defined assignments and deliverables
Guidance on data structure and organization
Feedback on accuracy and quality
Ongoing coordination with project leads
Work will be reviewed periodically to ensure quality, accuracy, and alignment with project standards.
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Feedback & Evaluation
Participants will receive feedback on:
Data quality and accuracy
Organization and structure
Attention to detail
Consistency and reliability
Ability to follow systems and improve workflows
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Professional Expectations
Participants are expected to:
Maintain organized and accurate work
Communicate clearly and professionally
Meet agreed-upon deadlines
Follow structured workflows and incorporate feedback
Demonstrate reliability and accountability in assigned responsibilities
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What You’ll Gain
Experience working with real-world project data
Exposure to structured data workflows
Development of practical data and systems skills
Experience contributing to multi-disciplinary teams
Professional feedback and mentorship
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Growth Opportunities
High-performing participants may be considered for:
Extended roles
Increased responsibilities
Future project involvement
Potential transition into long-term roles
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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 skills
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Summary Positioning Statement
This role is intended to function as a structured, educational, data-focused internship that provides hands-on experience in data organization, systems development, and real-world project workflows. It is designed to support academic learning while providing practical exposure to infrastructure and development initiatives.