Job Hunter - Automated Job Search System#

Build a complete job hunting system: LinkedIn scraper, match scorer, and Telegram bot with inline buttons.

What This System Does#

1. Scrapes real jobs from LinkedIn (public guest API, no login needed)
2. Scores each job 0-100% based on candidate profile (title, skills, experience, location)
3. Sends matching jobs to Telegram with action buttons (details, apply, remove)
4. Provides a clean foundation you can extend with CV generation later if needed

Setup Flow#

1. Gather Candidate Profile#

Ask the user for:

• Target roles (e.g. data analyst, BI developer, frontend developer)
• Core skills (e.g. SQL, Python, React, Power BI)
• Bonus skills (nice-to-have)
• Max years of experience they qualify for
• Preferred location and metro area cities
• Contact info (name, email, phone, LinkedIn URL)
• Work experience (companies, roles, dates, bullet points)
• Education (degree, institution, year)

2. Create Telegram Bot#

Guide the user:

1. Open Telegram, search for @BotFather
2. Send /newbot, choose a name and username
3. Copy the bot token
4. Get their Telegram user ID (send a message to @userinfobot)
5. Optionally add more authorized users (e.g. the job seeker)

3. Deploy the System#

Create a project directory and deploy these scripts (from scripts/):

text

job-hunter/
├── config.json          # Bot token, user IDs, candidate profile
├── jobs.db              # SQLite database (auto-created)
├── scorer.py            # Match scoring engine
├── linkedin_scraper.py  # LinkedIn job scraper
├── bot.py               # Telegram bot with inline buttons
└── notify_new_jobs.py   # Send new matches to Telegram

config.json Structure

json

{
  "telegram_bot_token": "TOKEN_FROM_BOTFATHER",
  "telegram_user_id": 123456789,
  "authorized_users": [123456789],
  "notify_users": [123456789],
  "candidate": {
    "name": "Full Name",
    "email": "email@example.com",
    "phone": "054-1234567",
    "linkedin": "linkedin.com/in/username",
    "location": "Tel Aviv, Israel",
    "target_titles": ["data analyst", "bi developer"],
    "good_titles": ["business analyst"],
    "core_skills": ["sql", "python", "power bi"],
    "bonus_skills": ["etl", "dax", "pandas"],
    "max_years": 2,
    "preferred_locations": ["tel aviv", "herzliya", "ramat gan"],
    "metro_locations": ["petah tikva", "rishon lezion"]
  }
}

4. Customize Scripts#

After copying scripts from scripts/, customize:

• scorer.py - Update PROFILE dict with candidate's profile from config.json
• linkedin_scraper.py - Update DEFAULT_QUERIES with relevant search terms
• bot.py - Should work with just config.json changes
• notify_new_jobs.py - Verify notification flow and recipients

5. Install Dependencies#

Install Python dependencies required by the included scripts. At minimum, verify the libraries imported by the scraper and bot are available in your environment.

6. Initialize Database#

The database auto-creates on first run. Schema:

sql

CREATE TABLE jobs (
    job_id TEXT PRIMARY KEY,
    title TEXT, company TEXT, location TEXT,
    url TEXT, career_url TEXT,
    description TEXT, requirements TEXT,
    required_years INTEGER,
    published_date TEXT, found_date TEXT,
    status TEXT DEFAULT 'new'
);

7. Start the Bot#

bash

nohup python3 -u bot.py > bot.log 2>&1 &

8. Set Up Daily Search (Cron)#

bash

# Run daily job search + notify at 9 AM
0 9 * * * cd /path/to/job-hunter && python3 linkedin_scraper.py && python3 notify_new_jobs.py

Or use OpenClaw cron:

text

openclaw cron add --name daily-job-search --schedule "0 9 * * *" --prompt "Run job search and notify"

Bot Commands#

CommandWhat it does/topShow top jobs (score >= 60%)/jobsList all jobs with scores/searchTrigger new LinkedIn search/statsShow statistics/appliedShow applied jobs/helpShow commands

Scoring Weights#

FactorPointsLogicTitle match0-30Perfect match = 30, partial = 15Skills match0-30Core skills = 5 each (max 20), bonus = 2 each (max 10)Experience0-400yr = 40, 1yr = 30, 2yr = 10, 3+ = -20Location0-25Preferred = 25, metro = 15, country = 5Junior keywords0-10Entry-level indicators

Thresholds: 🟢 >= 70% apply | 🟡 >= 50% review | 🔴 < 50% skip

Troubleshooting#

• Bot not responding: Check only ONE instance is running ( ps aux | grep bot.py)
• 409 Conflict: Multiple bot instances. Kill all, restart one.
• No jobs found: Check search queries match real LinkedIn job titles
• Scoring too high/low: Adjust weights in scorer.py