Investment Support

Lightcast provides detailed job posting and skills data that supports capital market analysts and investors in evaluating sector vitality and company performance. These insights help identify growth signals, assess workforce demand, and inform more strategic investment decisions.

Sector Trends & Corporate Health via Skills Analysis

Skills Demand Insights

Lightcast job posting data captures a broad spectrum of skills from foundational competencies to highly specialized technical capabilities. Analyzing how these skills appear and evolve across sectors provides insight into current conditions and emerging market trends.

For example, a rise in postings requiring cybersecurity skills may signal increased investment in data protection and risk management.

Technological Adoption & Innovation

Demand for specific programming languages, platforms, and software tools in job postings serves as a direct indicator of technological adoption.

Tracking these requirements helps assess innovation levels within sectors and anticipate future growth and competitive positioning.

Company Analysis with Integrated Identifiers

Linking Financial and Workforce Data

By using identifiers such as stock tickers, FIGI IDs, and exchange information, Lightcast enables analysts to connect job posting trends directly with financial performance metrics. This integrated view offers deeper insight into company health and market potential.

Comprehensive Data Mapping

The inclusion of LinkedIn URLs and other digital identifiers supports a more complete analysis of workforce dynamics and corporate strategy. These signals help explain how companies position themselves and adapt to changing economic conditions.

Strategic Application of Insights

Combining job and skills data with financial metrics allows market participants to build more nuanced investment strategies using timely workforce signals to identify opportunities and manage risk more effectively.

Optimal Data Delivery Mechanisms

Efficient Access Through Snowflake

Lightcast uses Snowflake Direct Shares to provide clients with direct access to the latest job posting and skills data within their existing environments. This approach supports immediate analysis without the need for data duplication or complex transfers.

Flexible Integration via Bobsled

For clients requiring broader data access, Lightcast also supports Bobsled and other direct-sharing mechanisms. These options enable seamless integration across multiple cloud platforms, ensuring timely access to data and supporting agile, up-to-date market and investment analysis.

Lightcast’s approach to job posting and skills data offers a foundational tool for financial analysts and investors, providing a dynamic and detailed view of market trends and corporate strategies through sophisticated data integration and delivery systems. This data is instrumental in crafting informed, strategic decisions in the capital markets.

Caveats in Big Data & Point-in-Time Clarity

Lightcast job posting data includes certain fields that are point-in-time, meaning their values remain unchanged after the initial ingestion of a posting. These fields preserve the original state of the data, even as the broader dataset is refreshed over time.

Examples of point-in-time fields in the Job Postings table include:

POSTED
EXPIRED
COMPANY_RAW
TITLE_RAW
BODY

Point-in-Time Fields Explained

POSTED records the date a job was first published, and EXPIRED captures the date the posting was removed. Once set, these timestamps do not change, ensuring an accurate historical record of job availability and duration.

COMPANY_RAW and TITLE_RAW store the original, un-enriched company name and job title exactly as published. These fields are intentionally preserved to maintain fidelity to the original hiring entity and public-facing language.

BODY contains the full, raw job posting text from the source. This field remains unchanged and is especially valuable for clients who conduct independent text analysis using proprietary keyword logic or custom models.

Data Refresh Cadence

While some fields are point-in-time, Lightcast data as a whole is not inherently point-in-time:

Job postings are refreshed and enriched monthly
Profiles data is refreshed quarterly

As enrichment and classification improve, downstream attributes such as skills, titles, or company mappings may change between refreshes.

Creating Point-in-Time Datasets

For clients who require point-in-time consistency, Lightcast recommends:

Exporting job postings monthly
Exporting profiles data quarterly

These snapshots should be stored locally to preserve historical context and ensure reproducibility in longitudinal analysis.

To support this process, Lightcast provides pipeline run dates in the metadata tables. These timestamps enable clients to systematically capture and manage their own point-in-time datasets with confidence.

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For detailed explanation, see the article on Posting Deduplication.

Deduplication Process

Lightcast aggregates job postings from across the internet, which requires rigorous processes to identify and remove duplicate listings. Using a structured, two-step deduplication approach, Lightcast removes up to 80% of collected postings ensuring the data remains accurate and reliable for analysis.

Two-Steps Approach

Step 1: Source-Level Filtering

At the source level, Lightcast scraping systems identify new advertisements specific to each job board or source. These systems are designed to avoid collecting postings that have already been captured, ensuring that only unique listings are ingested during initial collection.

Step 2: Cross-Source Deduplication

Because the same job can appear on multiple sources, Lightcast performs cross-source deduplication using normalized fields such as:

Job title
Company
Location

This process runs over a 60-day window to capture reposting behavior across platforms.

Example: If a Marketing Specialist role at Google is first posted on March 1, that posting is treated as the original. Any identical postings found within the next 60 days are classified as duplicates. If the role is reposted daily for a year, it would be counted six times, as a new deduplication cycle begins every 60 days.

Frequency and Quality Controls

Deduplication runs daily
Processes are continuously reviewed and refined to maintain accuracy

For more complex scenarios such as slight title variations or minor text differences Lightcast applies advanced algorithms and manual review to ensure correct classification.

By applying these comprehensive deduplication methods, Lightcast delivers a clean, high-quality job posting dataset that supports confident, data-driven insights.

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Check out to this article to know more about All Active Job Postings

Job Posting Types

Lightcast measures job posting activity over time using two complementary metrics Newly Posted and Active. Together, these measures provide a clear and nuanced view of job market dynamics.

Newly Posted

Newly Posted captures all job postings that were first published within a specific month. This metric reflects current market behavior, showing how employer demand changes month over month.

Active

Active includes all postings that were live at any point during a given month, even if they were originally posted earlier.

Active postings rely on Lightcast’s expiration methodology, which ensures outdated listings do not skew results. In the United States, postings expire after 61 days unless validated as still active. Lightcast continually improves this validation process to better confirm posting status within the expiration window.

As expiration methods evolve and market conditions change, trends in active postings may shift. Improved accuracy can result in noticeable changes in historical trend lines.

How to Use These Metrics

Active postings represent the total open demand in a given month and are best suited for analyzing sustained hiring needs.
Newly posted postings highlight new hiring activity, making them ideal for understanding short-term market behavior and emerging opportunities.

By using both metrics together, Lightcast provides a more complete picture of employer demand capturing both ongoing hiring needs and newly emerging trends.

Company's Monthly Job Postings Query

One popular use case is calling for the monthly job postings count from a specific company (Microsoft).

Data Shares Used:

Job Postings
Companies

SQL Example:

-- Set the ticker symbol
SET ticker = 'msft';

-- Query to get monthly posting counts by company / ticker
SELECT 
    DATE_TRUNC(MONTH, posted) AS pst_mth,
    COUNT(id) AS pst_cnt
FROM 
    lightcast.global.postings
WHERE 
    company IN (
        SELECT id 
        FROM lightcast.taxonomy.company
        WHERE 
            version IN (
                SELECT value 
                FROM lightcast.global.postings_meta 
                WHERE key = 'company_version'
            )
            AND tickersymbol IS NOT NULL
            AND tickersymbol = $ticker
    )
    AND posted >= '2024-03-01'
GROUP BY ALL 
ORDER BY 
    pst_mth ASC;