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agenthustler
agenthustler

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How to Build a Job Offer Negotiation Tool with Salary Data

#webdev #programming #python #tutorial

The Salary Data Gap

Most job seekers negotiate blind. Lets build a Python tool that scrapes salary data and creates negotiation briefs with percentile ranges.

Setup 

pip install requests beautifulsoup4 pandas numpy
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Salary sites have anti-bot measures. ScraperAPI handles JavaScript rendering and CAPTCHAs.

Scraping Salary Data 

# Implementation is proprietary (that IS the moat).
# Skip the build — use our ready-made Apify actor:
# see the CTA below for the link (fpr=yw6md3).
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Multi-Source Aggregation 

def aggregate(job_title, location):
    sources = [scrape_salary_data(job_title, location)]
    all_data = pd.concat([df for df in sources if not df.empty])
    return {
        "median": all_data["total_comp"].median(),
        "p25": all_data["total_comp"].quantile(0.25),
        "p75": all_data["total_comp"].quantile(0.75),
        "p90": all_data["total_comp"].quantile(0.90)
    }
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Negotiation Brief Generator 

def generate_brief(job_title, location, offer):
    stats = aggregate(job_title, location)
    print(f"Role: {job_title} in {location}")
    print(f"Your Offer: ${offer:,.0f}")
    print(f"Market: P25=${stats[p25]:,.0f} Med=${stats[median]:,.0f} P75=${stats[p75]:,.0f}")
    if offer < stats["median"]:
        print(f"Below median. Target ${stats[median]:,.0f}-${stats[p75]:,.0f}")
    elif offer < stats["p75"]:
        print(f"Competitive. Push for ${stats[p75]:,.0f}")
    else:
        print("Strong offer. Negotiate perks.")

generate_brief("Senior Software Engineer", "San Francisco", 185000)
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Proxy Strategy

Use ThorData residential proxies for sites blocking datacenter IPs. Monitor with ScrapeOps.

Extending the Tool

  • Equity valuation with RSU vesting schedules
  • Cost of living normalization across cities
  • Trend analysis tracking quarterly salary changes
  • Company-specific drilldowns

Conclusion

Data-driven negotiation beats guessing. ScraperAPI makes gathering salary data at scale practical and reliable.

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