Building PayPal's skill-level talent intelligence with Claude

~24400

Employees

$31.8B

Revenue

Financial Technology

Industry

San Jose, U.S.

Headquarters

The Core Challenges

Skills mapping and adjacency
Strengthen workforce planning through advanced skills mapping and adjacency insights.
Skill-level labor-market intelligence
Gain deeper skill-level labor-market intelligence to support sourcing, development, and retention.
Continuous skills analytics
Enable continuous skills analytics for long-term workforce evolution.
Research speed
PayPal's talent team needed richer skill-level market intelligence and faster research to support workforce planning, sourcing, development, and retention in a competitive fintech talent market.
OUTCOME
Faster, deeper skill-level intelligence, with talent research consolidated into one platform
Research that once took days was cut, and PayPal's talent team gained the skill-level and labor-market intelligence to plan workforce moves across global teams.

What we did

Draup gave PayPal's talent team skill-level analysis, enhanced reporting, and market intelligence, with Claude Cowork and Claude Code accelerating the research behind it.

PayPal wanted to strengthen workforce planning through advanced skills mapping and adjacency insights, gain deeper skill-level labor-market intelligence, and enable continuous skills analytics for long-term workforce evolution. Draup provided skill-level analysis, enhanced reporting, and market intelligence to support data-driven talent planning across global teams.

Behind that work, Draup's consulting team used Claude, via Claude Cowork and Claude Code, to accelerate skill-level research, synthesize labor-market signals, and prepare client-ready reporting. Claude was also used extensively to generate quick quality checks of the labor market parameters and to find loopholes in the overall strategy Draup was proposing.

Claude in the workflow

Draup's consulting team used Claude Cowork and Claude Code to accelerate the skill-level research behind the engagement and to check the strategy Draup was proposing for loopholes.

Claude Cowork & Claude Code
Skill-level research and labor-market synthesis
Accelerated skill-level research and synthesized labor-market signals into the intelligence PayPal's talent team needed for planning, sourcing, development, and retention.
Research that once took days
Claude Cowork & Claude Code
Client-ready reporting
Prepared the client-ready reporting on skill-level analysis, skill adjacencies, and market intelligence that Draup delivered to PayPal.
Enhanced reporting
Claude Cowork & Claude Code
Quality checks and strategy review
Generated quick quality checks of the labor market parameters and looked for loopholes in the overall strategy Draup suggested.
Strategy checked for loopholes

Outcomes

Research that took days, accelerated

PayPal accelerated talent research that previously took days.

Deeper skill-level intelligence

The talent team gained deeper skill-level and labor-market intelligence for sourcing, development, and retention.

Faster, data-driven workforce planning

Faster, data-driven workforce planning across global teams.

A more future-ready workforce

Skill-level intelligence and continuous skills analytics now support a more future-ready workforce.
Draup's Ecosystem feature significantly reduces our research time, allowing for quicker access to actionable talent insights. Now, with everything consolidated under one platform, we can easily explore ecosystems in any location. This efficiency drastically speeds up research that would otherwise take days.
Sam Fletcher
Former Head of Talent Intelligence
6,100+​
Locations
4M+​
Career Paths​
1.7M+​
Peer Group Companies​
28K+
Skills
3,500+​
Roles
1B+​
Professionals​
55K+​
Universities​
1B+​
Job Descriptions​
200K+​
Courses​
180K+​
Technology Solutions​
1.6M+​
Account Priorities​
Labor Market Data Contextualized with Business Intelligence for Every Decision

Analyzing 1B+ data points
daily from 100K+ sources

6,100+​
Locations
4M+​
Career Paths​
1.7M+​
Peer Group Companies​
28K+
Skills
3,500+​
Roles
1B+​
Professionals​
55K+​
Universities​
1B+​
Job Descriptions​
200K+​
Courses​
180K+​
Technology Solutions​
1.6M+​
Account Priorities​
SOC 2
GDPR
CCPA
ISO 27001
ISO 42001
EAIGG

Ethical AI, Backed by Global Standards

Draup, an AI-first company, upholds global standards like SOC 2, GDPR, CCPA, ISO 27001, and ISO 42001. As an EAIGG member, we audit for bias and build trustworthy AI.

Data Trust &
Methodology
at Draup

Draup uses a structured methodology to reduce inaccuracies and prevent misleading information, with a focus on transparency and responsible data practices.

Data Transparency and Coverage

Draup sources data from diverse, vetted global inputs including public datasets, labor information, professional ecosystems, and industry research. Coverage varies by region and role, and we supplement limited areas with alternative sources and analyst-led modeling.

Profiles Behind the Numbers

All aggregate insights related to buyers, roles, skills, and locations are grounded in structured, anonymized human and organizational profiles rather than pure extrapolation. This ensures context, reliability, and protection of personal identities.

Data Hygiene and Integrity

We maintain a clean, accurate data environment by removing duplicates, outdated entities, and invalid records. Automated checks powered by ML models and analyst reviews work together to ensure clarity and accuracy for every entity, such as buyer, role, skill, technology, or company.

AI Governance and Bias Mitigation

Our governance framework combines automated evaluations with Human-in-the-Loop reviews. We use statistical checks, audits, and cross-source comparisons to reduce demographic and structural bias before insights reach the platform.

Compensation Guardrails

Compensation insights use blended, directional inputs such as aggregated ranges, benchmarks, modeled distributions, and market signals. We distinguish clearly between modeled and reported data and apply guardrails to prevent over-interpretation.

Hourly and Frontline Workforce Coverage

For hourly, frontline, and blue-collar roles where digital visibility is limited, we incorporate government datasets, localized labor information, and specialized partners to build a more complete and balanced view of workforce supply and demand.

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