Job Description

JOB DESIGN

Role:

University Data Research & Structuring Intern

Function:

Global Education Data Operations

Reporting To:

Project Lead

Purpose Level:

Mission-critical (Database Accuracy & Trust)

1. ROLE PURPOSE (WHY THIS ROLE EXISTS)

To build and maintain a

clean, verified, structured master database of global universities and courses

, enabling students to access accurate academic information in one place.

This role exists to:

Eliminate fragmented, unreliable education data Convert unstructured university website information into

platform-ready data

Maintain long-term

data credibility

for the product Product development in edtech Learning operations & entrepreneurship. Work along with founder at founders office.

Non-goal:

This role is NOT for content writing, SEO blogging, or promotional research.

2. ROLE SCOPE (WHAT THE INTERN IS RESPONSIBLE FOR)

Included in Scope

Data extraction from

official university sources

Data validation and cross-verification Standardised data entry into master templates Flagging inconsistencies and missing data Documentation of sources and updates

Explicitly Excluded

Making assumptions when data is unclear Writing descriptive or marketing content Communicating with universities unless authorised Changing schema or formats independently

3. DATA DOMAINS OWNED BY THE ROLE

The intern will work across the following

fixed data blocks

:

A. University-Level Data

University name (official) Country, state, city Establishment year Type (public / private) Accreditation bodies Official website URLs Global / national rankings (approved sources only)

B. Course-Level Data

Degree level (UG / PG / PhD / Diploma) Course name (official title) Specialisation Duration Mode of study Intake months Entry requirements Language requirements Tuition fees Currency Fee period (annual / total)

C. Metadata

Source links (mandatory) Last verified date Notes / exceptions

4. WORKFLOW DESIGN (HOW THE WORK IS DONE)

Step 1: Assignment Allocation

Intern receives:

Country / university list Approved data sources Data template Output deadline
No self-selection of universities.

Step 2: Source Identification

Allowed sources (priority order):

Official university website Government / accreditation portals Approved ranking bodies

Rule:

If data is not available on official sources ? mark as "Not Available", do not guess.

Step 3: Data Extraction

Extract raw data carefully Match data to predefined schema Preserve original terminology where required Note country-specific variations separately

Step 4: Data Structuring & Standardisation

Convert raw information into platform format Standardise: Degree names Durations Intake cycles Fee structures Follow naming conventions strictly

Step 5: Verification

Cross-check critical fields: Course availability Fees Entry requirements Validate URLs Check for outdated pages

Step 6: Submission & Review

Submit completed batch Attach source links Highlight anomalies Await feedback before next batch

5. CONTROLS & RULES (NON-NEGOTIABLE)

Data Accuracy Rules

No assumptions No copy-paste without understanding context No third-party agent websites

Formatting Rules

Follow schema exactly No free-text improvisation No inconsistent naming

Communication Rules

Ask questions early Flag unclear data instead of filling blanks Maintain audit trail

6. SKILL & COMPETENCY DESIGN

Core Competencies (Must-Have)

Research discipline Pattern recognition Attention to detail Structured thinking Academic comprehension MS office: Basics

Behavioural Traits (Critical)

Patience Process adherence Feedback receptiveness Low ego, high precision Comfort with repetitive accuracy-focused tasks

7. PERFORMANCE METRICS (HOW SUCCESS IS MEASURED)

Primary KPIs

Data accuracy rate (target: >95%) Schema compliance rate Error recurrence frequency Source documentation completeness

Secondary KPIs

Turnaround time per university Responsiveness to corrections Ability to handle complex data cases

Speed is evaluated only after accuracy stabilises.

8. GROWTH PATH

High-performing interns can move into:

Research Associate - Global Education Data Analyst - Education Platforms Product Data Specialist
This gives the role seriousness and retention value.

Job Type: Internship
Contract length: 3 months

Pay: ?1,000.00 - ?2,000.00 per month

Benefits:

Flexible schedule Internet reimbursement
Work Location: In person