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Data Analyst

Exclusive opportunity

Onsite

Data Analyst

Cardless

Data Analyst

Skills

SQL QueriesLookerTableauPythonData AnalysisAICompliance

2 months ago

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Important information


Contract type:

Permanent

Salary:

$130,000 – $200,000 / year

Location:

San Francisco, CA, USA

Work mode:

Onsite

Published on:

29 August 2026

What they need


  • Cardless is looking for a Data Analyst / Senior Data Analyst to join our team and help shape the insights, processes, and decisions behind our co-branded credit card platform
  • As an analyst at Cardless, you’ll dive deep into data, identify opportunities, streamline operational processes, and collaborate closely with cross-functional teams to deliver insights and durable improvements to our platform
  • In this role, you’ll work across domains including applications, accounts, transactions, fraud, risk, rewards, and partner operations to support high-impact initiatives and ensure the reliability, accuracy, and efficiency of our core systems and business workflows
  • Analyze operational, product, and financial data to identify trends, diagnose issues, and surface actionable insights
  • Build dashboards, reporting frameworks, and monitoring tools that improve visibility into system and business performance
  • Partner with product managers, engineers, and risk/compliance teams to support the design of new features, workflows, and policies
  • Evaluate and optimize business processes across the customer lifecycle (applications, onboarding, transactions, servicing, fraud, and rewards)
  • Perform deep-dive investigations into anomalies, system issues, or partner escalations; help determine root causes and drive remediation
  • Support forecasting, business reviews, and strategic planning with clear, data-driven analysis
  • Contribute to improving data quality, documentation, and analytical rigor across the organization
  • For senior candidates: provide guidance to teammates, lead medium-sized cross-functional projects, and influence strategic decisions

Benefits

  • 💸 Competitive salaries, equity, and a 401(k) plan
  • 🏥 Top-of-the-line healthcare (medical, vision, and dental), with 100% primary coverage and 75% dependent coverage for medical
  • 🌴 Unlimited paid time off, with a minimum of 15 days off per year
  • 👶 Parental leave for birthing and non-birthing parents
  • ✈️ Team trips & offsites
  • For in-office employees:
  • 🍱 Catered lunch at the office every day, plus plenty of snacks & drinks
  • 🚎 $250/month commuter assistance for public transit or our parking garage
  • For remote employees:
  • 🖥️ $500 remote setup stipend to help you do your best work- Curiosity, attention to detail, and a passion for building well-structured analytical systems and business processes
  • Demonstrated ability to integrate AI into day-to-day work (prompt design, model evaluation, data prep, or workflow optimization)
  • Excellent communication skills — able to translate complex analysis into clear insights for technical and non-technical partners
  • Strong proficiency with data analysis tools (SQL, Excel/Sheets, Python)
  • Ability to manage multiple priorities, take ownership, and drive projects end-to-end
  • Bonus: experience in fintech, credit/financial systems, fraud, risk, or customer lifecycle analytics
  • Experience using AI tools in a professional setting (e.g., for workflows, analysis, automation, or insight generation)
  • 3–7 years of experience in an analytical, operations, strategy, or data-focused role
  • Track record of collaborating effectively with product, engineering, or operations teams
  • Solid understanding of business processes, KPIs, and analytical frameworks; able to independently break down ambiguous problems
  • Experience working with large datasets and building reliable reporting/dashboarding (Looker, Tableau, Omni, Mode, or similar)
  • Experience in fintech, credit/financial systems, fraud, risk, or customer lifecycle analytics
  • Familiarity with financial systems, reconciliation workflows, or data integrity challenges
  • Experience building or deploying internal AI tools, automations, or agents to improve productivity or business operations

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