Cardless

Cardless

Head of Fraud Operations

San Francisco · Senior

Sponsorship not specified$170k-$230kDetected 204 days ago
SQLSparkLeadershipCommunication

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odds of building a lasting career here

59Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Files H-1B transfers

3 transfer filings in the last year, covering 3 workers. Median labor-condition decision: 8 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • You will be responsible for the people, processes, and tooling that make both run effectively.
  • This is a high-ownership role in a fast-growing environment.
  • Define clear performance standards, quality metrics, and career paths for analysts and investigators at each level.

Responsibilities

  • Cardless is building the infrastructure for the world's best companies to design, build, and launch financial products.
  • Companies like Coinbase and Bilt use Cardless to create credit cards that feel entirely their own.
  • Our APIs and components shape the journey from the first application to every purchase, reward, and moment of support that follows, while we handle lending, compliance, and operations behind the scenes.
  • Reporting to our Chief Risk Officer, you'll own two critical functions: manual review operations and fraud investigations.
  • You'll be expected to drive operational excellence today while building the foundation for a fraud ops function that scales with Cardless.
  • Build, manage, and develop a team of fraud analysts and investigators: responsible for hiring, onboarding, training, scheduling, and performance management.
  • ✈️ Team building events & happy hours
  • We're in the office at least three days a week, and most of us are there more than that, because we do our best thinking and building together in person.

Requirements

  • 7-12 years of experience in fraud operations, fraud investigations, or related functions at a financial institution, fintech, or payments company.
  • Excellent communication skills: you can write a crisp SOP and present operational performance to executives with equal ease.

Skills

  • Proactive, bias-to-action mindset:
  • Actual compensation is influenced by a wide array of factors, including but not limited to skills, experience, and specific work location.
  • We're proud to offer our team excellent
  • manual review operations and fraud investigations.

Compensation

  • This role has an annual starting salary range of $170,000 - $230,000 + equity + benefits (see below).
  • Actual compensation is influenced by a wide array of factors, including but not limited to skills, experience, and specific work location.

Benefits

  • We're proud to offer our team excellent benefits:
  • 💸 Meaningful Start-up equity
  • 🏥 100% health, vision & dental primary coverage
  • ➕ 75% health, vision & dental dependent coverage
  • 🚎 $250/month Commuter benefit
  • 👶 Parental leave
  • 🌴 Flexible PTO with a minimum of 15 days off per year
  • We see what could be improved, make it so, and leave every product, system, and team better than we found it.

Company info

  • We're looking for kind, humble people with high standards and low egos.
  • We're looking for someone who's genuinely excited to be there alongside the team.
  • We're looking for a Head of Fraud Operations to build and lead the operational core of our fraud function.
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This listing is sourced directly from Cardless's careers page and normalized into a canonical job model.