Filter a Dataset Intelligently

Add the everyrow connector if you haven't already. Then upload hn_jobs_screen.csv and ask Claude:

Screen to find job postings that meet ALL THREE criteria: 1. Remote-friendly: explicitly allows remote work, hybrid, WFH, distributed teams, or "work from anywhere". 2. Senior-level: title contains Senior/Staff/Lead/Principal/Architect, OR requires 5+ years experience, OR mentions "founding engineer". 3. Salary disclosed: specific compensation numbers are mentioned. "$150K-200K" qualifies. "Competitive" or "DOE" does not.

Of 3,616 postings, about 230 pass the filter (6.4%). Results take about 8 minutes.

Ask Claude Code to filter job postings for remote, senior roles and it will write solid Python with keyword matching. But "remote-friendly" is not always a keyword. A posting might say "team distributed across three time zones" or "occasional office visits in SF." Screening 3,616 rows with that level of judgment needs per-row LLM evaluation.

Here, we get Claude Code to screen 3,616 job postings for "remote-friendly, senior-level roles with disclosed salary": three rules that require reading each posting.

Add everyrow to Claude Code if you haven't already:

claude mcp add futuresearch --scope project --transport http https://mcp.futuresearch.ai/mcp

Download the dataset: hn_jobs_screen.csv (3,616 Hacker News "Who's Hiring" posts, March 2020 through January 2026). With the CSV in your working directory, tell Claude:

Screen hn_jobs_screen.csv to find job postings that meet ALL THREE criteria:

1. Remote-friendly: explicitly allows remote work, hybrid, WFH, distributed
   teams, or "work from anywhere"
2. Senior-level: title contains Senior/Staff/Lead/Principal/Architect, OR
   requires 5+ years experience, OR mentions "founding engineer"
3. Salary disclosed: specific compensation numbers are mentioned.
   "$150K-200K" qualifies. "Competitive" or "DOE" does not.

Claude calls everyrow's screen MCP tool with your criteria, then polls for progress until the operation completes:

Tool: everyrow_screen
├─ task: "Find job postings that meet ALL THREE criteria: 1. Remote-friendly..."
├─ input_csv: "/Users/you/hn_jobs_screen.csv"
└─ response_schema: null

→ Submitted: 3,616 rows for screening.
  Session: https://futuresearch.ai/sessions/b47f3d3d-...
  Task ID: 8a2f...

Tool: everyrow_progress
├─ task_id: "8a2f..."
→ Running: 0/3616 complete, 3616 running (18s elapsed)

Tool: everyrow_progress
→ Running: 1204/3616 complete, 2412 running (142s elapsed)

...

Tool: everyrow_progress
→ Completed: 3616/3616 (0 failed) in 478s.

Tool: everyrow_results
├─ task_id: "8a2f..."
├─ output_path: "/Users/you/qualified_jobs.csv"
→ Saved 232 rows to /Users/you/qualified_jobs.csv

Under the hood, everyrow runs a two-pass pipeline: a fast first pass triages all 3,616 rows (gemini-3-flash-preview, 12.7M tokens, $10.89), then a careful second pass re-evaluates the borderline cases with a stronger model (claude-sonnet-4, 224K tokens, $0.13).

232 of 3,616 postings passed (6.4%). View the session.

The data reveals a clear trend in tech hiring over the pandemic years:

In early 2020, only 1.7% of postings met all three criteria. By 2025, 14.5% did. More companies now offer remote work, disclose salaries upfront, and hire senior engineers through Hacker News.

Sample qualified postings:

Bloomberg | Senior Software Engineer | Hybrid (NYC) | $160k - $240k USD + bonus
KoBold Metals | Senior Infrastructure Engineer | Remote (USA) | $170k - $230k
EnergyHub | Director of Engineering | Remote (US) | Salary $225k
Gladly | Staff Software Engineer | Remote (US, Colombia) | $60k–$215k + Equity

The everyrow Python SDK orchestrates thousands of parallel LLM evaluations in a single function call, for filter criteria that require judgment on every row.

Here, we screen 3,616 job postings for "remote-friendly, senior-level roles with disclosed salary": three criteria that can't be reduced to pattern matching.

pip install everyrow
export EVERYROW_API_KEY=your_key_here  # Get one at futuresearch.ai/api-key

To follow along, right click this link and save the CSV file to your computer (3,616 Hacker News "Who's Hiring" posts, March 2020 through January 2026).

import asyncio
import pandas as pd
from pydantic import BaseModel, Field
from everyrow.ops import screen

jobs = pd.read_csv("hn_jobs_screen.csv")  # 3,616 job postings

class JobScreenResult(BaseModel):
    qualifies: bool = Field(description="True if meets ALL criteria")

async def main():
    result = await screen(
        task="""
        A job posting qualifies if it meets ALL THREE criteria:

        1. Remote-friendly: Explicitly allows remote work, hybrid, WFH,
           distributed teams, or "work from anywhere".

        2. Senior-level: Title contains Senior/Staff/Lead/Principal/Architect,
           OR requires 5+ years experience, OR mentions "founding engineer".

        3. Salary disclosed: Specific compensation numbers are mentioned.
           "$150K-200K" qualifies. "Competitive" or "DOE" does not.
        """,
        input=jobs,
        response_model=JobScreenResult,
    )

    qualified = result.data
    print(f"Qualified: {len(qualified)} of {len(jobs)}")
    return qualified

qualified_jobs = asyncio.run(main())

216 of 3,616 postings passed (6.0%). View the session.

The data reveals a clear trend in tech hiring over the pandemic years:

In early 2020, only 1.7% of postings met all three criteria. By 2025, 14.5% did. More companies now offer remote work, disclose salaries upfront, and hire senior engineers through Hacker News.

Sample qualified postings:

Bloomberg | Senior Software Engineer | Hybrid (NYC) | $160k - $240k USD + bonus
KoBold Metals | Senior Infrastructure Engineer | Remote (USA) | $170k - $230k
EnergyHub | Director of Engineering | Remote (US) | Salary $225k
Gladly | Staff Software Engineer | Remote (US, Colombia) | $60k–$215k + Equity