Staff Analyst – Risk and Fraud Systems

Paddle

. Build data, decisioning and automated systems that enable Paddle to take more good risk while reducing fraud losses, customer friction and manual work .

Posted 11/11/2026full-timeRemote • United KingdomLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and improving fraud detection systems, utilizing SQL, Python, and statistical analysis to quantify risk trade-offs and enhance seller risk management. Capable of translating complex risk problems into actionable data-driven solutions with measurable outcomes.

Highest-signal resume keywords

Fraud Detection SystemsSQL ProficiencyPython ProgrammingRisk Score EvaluationDecision Flow Systems

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Fraud DetectionSQLPythonStatisticsBacktestingRisk ScoringData AnalysisVersion ControlImpact AnalysisMonitoring

Soft Skills

JudgmentCollaborationProblem-Solving

Tools & Technologies

SnowflakeDbtTactileLLMs

Industry Keywords

Merchant of RecordPaymentsMarketplaceFraud LossesCustomer Friction

Tech Stack

Tools & technologies

PythonSnowflakeSQL

About the role

Key responsibilities & impact

Build data, decisioning and automated systems that enable Paddle to take more good risk while reducing fraud losses, customer friction and manual work
Map the end-to-end seller risk system, including data, decisions, controls, owners and failure points
Establish baselines for fraud losses, alert yield, time-to-detect, exposure at detection and analyst effort, reconciled with Finance
Own the health of live controls, including ownership, expected volume, measured yield, alerting, testing and impact assessment
Build and maintain a labelled library of confirmed fraud cases and a shared fraud typology
Build a value-ranked portfolio of risk opportunities
Translate risk problems into product, data and engineering work with measurable acceptance criteria
Design seller risk tiers governing payout timing, reserves and limits
Backtest rules and risk scores using point-in-time data
Design control experiments, shadow tests and phased roll-outs measuring loss reduction and legitimate-customer impact
Produce decision artefacts for senior-leader trade-offs involving risk appetite, engineering investment, customer experience and commercial growth
Take major capabilities through production, establish long-term ownership and progress to the next high-value problem
Achieve six-month outcomes including materially improving a seller-risk journey, reducing repetitive screening for Fraud/Risk Operations and handing stable capabilities to durable owners

Requirements

What you’ll need

Significant experience building or improving merchant- or seller-side fraud detection at a PSP, acquirer, payfac, marketplace or Merchant of Record
Working knowledge of bust-out, transaction laundering and self-dealing in data
Fluency in SQL, including Snowflake, dbt or similar
Proficiency in Python and statistics
Experience using LLMs on unstructured data such as website content or support tickets, with measured accuracy
Experience with decision flow systems such as Tactile
Experience turning ambiguous cross-functional problems into adopted systems with measurable results
Experience designing, backtesting and tuning rules and risk scores on point-in-time data
Experience evaluating rules and risk scores with delayed, partial and adversarial labels
Experience with version control, testing, impact analysis, monitoring, drift detection and audit trails for production controls
Ability to quantify risk trade-offs in fraud losses, approval rates, customer friction, operating cost and revenue using a Finance-approved method
Judgment to select appropriate rules, workflows, experiments, vendors, models or agents
Ability to work with investigators, operators, product managers, engineers, data scientists and executives
Experience in a Merchant of Record, payments, marketplace, subscription or other adversarial transactional environment is useful but not mandatory
No specific educational credential required; Paddle states it does not care where candidates studied

Benefits

Comp & perks

Stock options
Unlimited holidays
Enhanced parental leave
Retirement plans
Private healthcare
Well-being initiatives
Annual learning fund
Regular internal and external training
Flexible choice of where, when and how to work within hub locations
Trust and autonomy in working arrangements
Global hubs for focused collaboration