For Sales and Agencies

A point-in-time labor dataset, built for alpha.

Hiring is the earliest signal a company sends. Before earnings calls, before press releases, before the 10-K — companies tell you what they're going to do by who they hire. HireBase turns 200,000+ public career pages into a clean, deduplicated, point-in-time-accurate hiring dataset built for quantitative funds, fundamental analysts, and data desks.

Global job market
Millions of job data
Real time
35+
Data fields
Hiring Velocity
200K+
Companies tracked
Data Freshness
< 3hr
Indexed: Product Designer @ Airbnb
Indexed: Staff Eng @ Linear
Indexed: Head of Sales @ Ramp
Indexed: Backend Dev @ Stripe
Indexed: AI Researcher @ OpenAI
Indexed: Product Designer @ Airbnb
Indexed: Staff Eng @ Linear
Indexed: Head of Sales @ Ramp
Why Hiring Data

Competitive intelligence built on direct-from-source hiring data.

Every competitor pivot, every new market, every product roadmap shift leaks first into job postings. By the time a strategic move hits TechCrunch, it's been encoded in their hiring patterns for months. Here's what to watch — and what each pattern means.

Hiring velocity

First-seen and last-seen timestamps on every role mean you can compute exact open-role flow, net opens minus closures, and rolling 30/60/90-day velocity per company, sector, or function.

Example:A fintech's net role flow inflected positive 47 days before its Series F announcement.

Geographic expansion

Detect new market entry months ahead of announcements. Geocoded role data shows which cities, countries, and regions are getting investment — and which are being quietly wound down.

Example:A US fintech opened 47 roles in Mexico City three months before announcing LATAM launch.

Function mix shifts

A surge in "Forward Deployed Engineer" roles signals enterprise focus. A wave of "Applied Research" hires signals AI investment. Function mix is the leading indicator of strategy shifts.

Example:Tracking AI/ML role share by company exposes which incumbents are catching up — and which aren’t.

Tech stack adoption

AI-extracted skills and tools across millions of postings. Watch enterprise adoption curves of any specific technology — Snowflake, Databricks, Kubernetes, OpenAI APIs — at the company level.

Example:Mentions of “Cursor” in F500 engineering JDs grew 11x in 6 months — a buy signal for dev-tool incumbents.

Hiring freezes & contraction

A drop in active postings, combined with role-removal events tracked in the historical archive, surfaces hiring freezes weeks before they’re announced or RIF disclosures hit.

Example:A consumer co’s net role flow inflected negative 6 weeks before a 12% RIF disclosure.

Compensation benchmarks

Millions of posted salary points across roles, levels, and geographies. Track compensation inflation in real time — by industry, function, or specific employer — months ahead of official statistics.

Example:Senior backend salaries in NYC fintech rose 9% YoY in posted comp data, 4 months before BLS print.
The Signal

Three ways to query the dataset.

Work at the level that fits your research. Pull individual records for backtesting, query pre-computed signals through the Insights API, or filter at the company level for portfolio screening and lead generation. 

Job records

Pull raw, enriched, point-in-time job records with first-seen and last-seen timestamps. The atomic unit. Best for building your own factors and running custom aggregations against the historical archive.

Best For
  • custom factor research
  • full-control backtesting
  • derivative datasets

Insights API

Pre-computed hiring velocity, salary trends, function-mix shifts, and geographic flow signals queryable per company, sector, or universe. Skip the aggregation step and pull the signal directly into your model.

Best For
  • rapid signal prototyping
  • dashboards
  • single-line factor pulls

Job records

Query 200,000 enriched company profiles by industry, services, technology stack, geography, and hiring activity. Identify companies entering new markets, scaling specific functions, or matching your investment criteria without processing individual job records.

Best For
  • universe construction
  • screening
  • deal pipelines
Built for data desks & quant teams

Clean, point-in-time, research-ready.

For quantitative funds, fundamental analysts, and corporate research desks. HireBase delivers a clean, deduplicated hiring dataset with full historical depth back to 2023, structured for direct ingestion into your research stack.

Point-in-time accurate. Every record carries first-seen and last-seen timestamps, to the second. No retroactive rewrites. Backtest against the data as it actually existed on any given date.

Hiring velocity, ready to compute. Because we capture exact post and removal timestamps, you can derive role-flow velocity at any window — 7d, 30d, 60d, 90d — without reconstructing the data yourself.

Direct from source. Sourced from public company career pages and ATS platforms — not aggregator feeds. Cleaner, fresher, and free from the duplication that pollutes other vendors' datasets.

Entity-resolved. Every job links to a canonical company entity, ticker-mapped where the company is public. Industry codes, ATS-platform metadata, and geographic data join cleanly to your existing universe.

Delivered how you want it. REST API for live access, S3 drops in CSV / Parquet / JSON for daily syncs, or one-time CSV/Parquet exports for the full history. Sample data available under NDA.

Net role flow — sample companyFrom the dataset
Window:Rolling 30d net opensSource:First/last-seen events
+ opens0− closuresM-5M-4M-3M-2M-1NowInflection: net flow turns positive
Each bar represents net opens minus closures over a rolling 30-day window. Computed directly from first-seen / last-seen event timestamps. Run your own analysis with the sample dataset.
Methodology

A dataset built for research,
not retrieval.

Most "hiring data" providers resell aggregator feeds. We don't. Here's how we build, clean, and serve a dataset that holds up to a quant team's diligence.

[ 01 ] Sourcing

Direct from the source.

200,000+ public company career pages and 30+ ATS platforms (Greenhouse, Lever, Workday, Ashby, iCIMS, SmartRecruiters, and more), scanned 12–24x per day. No third-party aggregator feeds. No reposts. No staffing-firm noise.

[ 02 ] Point-in-time

First-seen, last-seen, no rewrites.

Every record is timestamped on first observation, to the second, and never retroactively edited. When a posting is removed from the source, we record that as a separate event with its own timestamp — and surface those removals through a dedicated expired jobs feed so you can run daily delta syncs and track role closures precisely.

[ 03 ] Deduplication

One canonical job per role.

Multi-stage deduplication: URL canonicalization, title normalization, JD content hashing, and company-resolved entity matching. The same listing across multiple ATS platforms collapses into a single canonical record — so velocity calculations and role-flow signals don't double-count.

[ 04 ] Entity resolution

Canonical company linkage.

Every company is canonicalized to a unique entity with industry codes, geography, ATS platform, and — where the company is public — a mapped ticker. Join-ready against your existing security master.

[ 05 ] Enrichment

50+ structured fields per role.

AI-extracted seniority, function, salary range, tech stack, benefits, visa status, education requirement, location with geocode. The data is research-ready, not raw text.

[ 06 ] Sourcing posture

Public data, defensible practice.

All records originate from publicly accessible career pages. We respect robots.txt directives and rate-limit responsibly. Full DDO available covering data licensing, sourcing methodology, and compliance documentation. Listed on Neudata →

Delivery

However your team works.

Whether you're prototyping a signal in a Jupyter notebook or piping daily deltas into your warehouse, we deliver in the format that fits your stack.

REST API
Sub-50ms · Live data
S3 Drop
CSV / Parquet / JSON · Daily
Expired Jobs Feed
Removal events · Daily delta
One-time Export
Full history · Custom cuts
vs. Alternatives

Why funds and research desks switch.

A side-by-side look at how HireBase compares to aggregator-derived job datasets and legacy alt-data vendors. The differences compound over time.

AGGREGATOR-DERIVED DATASETS
LEGACY ALT-DATA VENDORS
HIREBASE
01
Source
3rd-party feeds, repackaged
Mixed; often partial direct
Direct from 200k+ career pages & ATS
02
Freshness
24–72 hour lag
24-hour batch typical
Most jobs indexed in <1hr
03
Deduplication
Same role across 5+ feeds
Vendor-specific, opaque
Canonical, one record per role
04
Point-in-time accuracy
Often rewritten, look-ahead risk
Some vendors, not all
First/last-seen, append-only archive
05
Historical depth
Varies, often shallow
5+ years for some
~18M records since 2023, growing daily
06
Structured fields
Raw text, minimal parsing
10–20 fields typical
50+ AI-extracted, normalized fields
07
Entity linkage
Inconsistent company names
Partial; vendor universe
Canonical entities, ticker-mapped where public
08
Pricing
Cheap, often unusable
High annual minimums typical
Trial via API, custom enterprise terms
Built for

Who's using HireBase as signal
infrastructure.

Stop briefing leadership with quarterly Gartner reports and slide decks built last sprint. HireBase data flows into your existing BI stack — Looker, Tableau, Hex, Metabase, custom internal tools — and updates as the market does.

Quantitative funds

Power a Google-for-Jobs-class experience with sub-50ms structured search across every real opportunity on the internet. Skip the scrapers. Skip the cleanup. Ship the product.

Job to be doneEngineer labor-derived signals

Fundamental analysts

Backfill a new vertical or region with enriched listings on day one. Use our Export API to seed millions of jobs into your database, then keep it fresh with the expired-jobs feed.

Job to be doneBuild conviction before earnings

Private equity & VC

Feed resume text straight into the Semantic Search API and return ranked matches by meaning. Pair with company data for context-aware pitches. Built for copilots, coaches, and career agents.

Job to be donePressure-test the deal model

Quantitative funds

Power a Google-for-Jobs-class experience with sub-50ms structured search across every real opportunity on the internet. Skip the scrapers. Skip the cleanup. Ship the product.

Job to be doneLead the macro print

Fundamental analysts

Backfill a new vertical or region with enriched listings on day one. Use our Export API to seed millions of jobs into your database, then keep it fresh with the expired-jobs feed.

Job to be donePower your data product

Private equity & VC

Feed resume text straight into the Semantic Search API and return ranked matches by meaning. Pair with company data for context-aware pitches. Built for copilots, coaches, and career agents.

Job to be doneCompete above your weight
Diligence

The questions your data desk will ask.

We've been through DDQ with hedge funds, PE firms, and corporate procurement. Here's where we stand on the questions you'll be asked to answer internally before signing.

Sample data and full DDQ available on request under standard NDA. Also listed on Neudata for fund evaluators already running diligence through the platform.

Request full DDQ
  • Is the data sourced from public web pages?Yes
  • Does sourcing respect robots.txt?Yes
  • Is the dataset point-in-time accurate?Yes
  • Is data ever retroactively rewritten?Never
  • Are removals tracked with timestamps?Yes
  • Is PII collected from postings?No
  • S3 / API / export delivery available?All three
  • Sample data under NDA?30-day
  • Get Started

    See the data for yourself.

    Request a sample dataset, run your own analysis, and decide whether the signal fits your process.

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