OVERVIEW
We operate a job board dedicated to the education technology industry vertical. While we currently feature job listings from education-focused companies, we are now looking to expand our scope to include corporate employers hiring for relevant learning-focused roles.
PROBLEM
Many non-education companies regularly hire for roles such as:
- Trainer / Training Specialist
- Instructional Designer
- LMS Administrator
- Learning & Development (L&D)
- Instructional Technology
- Learning Experience Designer
However, these roles are often buried among thousands of unrelated listings on large corporate job boards. Our goal is to isolate and surface only the relevant learning and training jobs —not general roles like sales, finance, or IT.
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NEED
We're looking for a freelancer to help us build a targeted job scraping solution. The goal is to find, extract, and organize job listings that match our industry focus from large companies’ job boards or aggregators.
fyi: Our job board has a built-in aggregator that if given a specific job listing URL will sometimes a) ONLY aggregate the specific job listing, but sometimes will b) ALSO aggregate many unrelated job listings.
Our job board can successfully pull jobs from several existing ATSs and other Jobs Board.
ATSs:
BambooHR
Greenhouse
Lever
Workable
Workday
ADP
Playlocity
Cornerstone Ondemand
Dayforce HCM
Paycom
iCIMS
Ultipro
Prism HR
Job Boards:
LinkedIn Jobs
HealtheCareers.com Jobs
AngelList Jobs
eFinancialCareers.com
Theladders.com
JobsInSports.com
ProBlogger.com Jobs
Dribbble.com Jobs
When job seekers come to our job board we would want them to link out from our Job Board directly to the source job listing (and not from another aggregator Job Board.
Additionally, we would want to remove any unnecessary UTM codes that point to a referring job aggregators as the source. We want to link to the true source URL from our job board (and not the URL that includes the other aggregators referral info).
Phase 1: Discovery & Proof of Concept
1. Identify job sources (e.g., large corporate career sites, aggregator platforms) that consistently include roles with learning-focused titles.
2. Scrape only those listings whose job titles match keywords such as:
- "Trainer"
- "Training"
- "Instructional Design"
- "Instructional Designer"
- "LMS Administrator"
- "Learning Management System Administrator"
- "Learning*"
- "Learning & Development"
- "L&D"`
3. Capture the direct source URL for the job listing (from the company’s official job board or ATS... not LinkedIn, Indeed, etc.).
4a. (Either) Create a list of the source URLs our job board's aggregator can pull from, or
4b. Create a database (or local file if running the script locally) that includes the extracted key data fields (Job Title, Job Type (Full-time, Part-time, etc), Employer, Job Description snippet HTML, Compensation Low, Compensation High, Compensation Currency, Compensation Frequency, Job listings's Source URL, Location text, and Posting Date.
*Essentially, the (JobPosting) structured data for Google Job Search described @ https://developers.google.com/search/docs/appearance/structured-data/job-posting) our job board's aggregator can pull from.
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IDEAL FREELANCER
- Strong background in web scraping with tools like Scrapy, Puppeteer, or BeautifulSoup.
- Familiarity with ATS platforms (e.g., Workday, Greenhouse, Lever) and their job listing structures.
- Ability to filter and extract data based on keyword logic in job titles.
- Bonus: Experience working with job boards, aggregators, or recruitment platforms.
DELIVERABLES
*The full deliverables are TBD as there are some elements of the project that still need to be specified based on the best practice recommended by the freelancer.*
- A functioning script that that pulls learning-focused jobs from 1–3 initial sources (ATS / Job Board).
- A data file or feed containing only the relevant job listings with their source URLs.
- Ultimately a list (again whether 4a a list of specific job listing URLs or 4b a database / local file of the specific jobs' Google Job Search (JobPosting) structured data.
- Documentation for setup, usage, and any recommendations for scaling.
NEXT STEPS
If this interests you, please include:
- A brief explanation of how you’d approach the task.
- Relevant examples of past work (especially scraping or jobs-related data).
- An estimated timeline and budget for completing Phase 1.
We’re excited to expand the reach of our education job board by including learning and development roles from the broader corporate world—your expertise can help us get there.
