Senior Data Analyst – Fraud Intelligence

Sem Parar

. Structure and engineer transactional data: develop and maintain databases, pipelines, and data-processing procedures for API queries, ensuring the availability, quality, traceability, and timely updating of information required for preventive monitoring.

Posted 11/7/2026full-timeSão Paulo • BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Data Engineering and Analysis, with advanced proficiency in SQL and Python for developing and maintaining data pipelines and monitoring mechanisms. Capable of applying statistical techniques and machine learning for anomaly detection and fraud prevention in digital environments.

Highest-signal resume keywords

Data EngineeringSQLPythonBehavioral AnalysisAnomaly Detection

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnalysisBuilding PipelinesTransactional MonitoringApplied StatisticsAnalytical ModelingAutomationsMonitoring MechanismsIncident InvestigationRisk AnalysisMachine Learning

Soft Skills

Autonomous WorkCollaboration

Tools & Technologies

DatabricksREST APIsDatadogNew RelicSalt SecurityAkamai API SecurityCloudflare API ShieldWallarmCequenceImperva

Industry Keywords

Digital Fraud PreventionCybersecurityInformation SecurityAPI ProtectionPaymentsFintechBanksFinancial Institutions

Tech Stack

Tools & technologies

Cyber SecurityPythonSaltStackSQL

About the role

Key responsibilities & impact

Structure and engineer transactional data: develop and maintain databases, pipelines, and data-processing procedures for API queries, ensuring the availability, quality, traceability, and timely updating of information required for preventive monitoring.
Develop velocity monitoring and rules: create monitoring mechanisms and query counters based on different variables, identifying concentrations, recurring activity, and suspicious patterns across different time intervals.
Conduct behavioral analysis and anomaly detection: apply statistical techniques, data modeling, and algorithms to identify behavioral patterns, establish normality parameters, and detect deviations associated with high-volume queries, automated attacks, and attempts to exploit APIs.
Develop preventive automations and controls: create rules, alerts, and automated mechanisms to identify and respond to suspicious behavior, supporting the implementation of blocking, query throttling, additional authentication, and contingency measures in partnership with Technology and Security teams.
Monitor risks and investigate incidents: analyze suspicious events, investigate behavioral deviations, identify vulnerabilities and root causes of incidents, and propose corrective and preventive measures to reduce the recurrence of attacks and unauthorized queries.
Enhance journey security layers: assess opportunities to strengthen API identification, authentication, and protection mechanisms, proposing technological improvements and additional controls to prevent fraud and abuse across digital journeys.
Develop risk indicators and intelligence: build dashboards, indicators, and control-performance analyses, monitoring transaction volumes, alerts, incidents, rule effectiveness, and false positives to support decision-making and improvement prioritization.
Drive automation, artificial intelligence, and continuous improvement: identify and implement opportunities to automate processes and apply artificial intelligence and machine learning to detect anomalous behavior, optimize rules, and improve the efficiency of prevention processes.
Support technical integration and control governance: work in partnership with Fraud Prevention, Technology, Information Security, and business teams, supporting solution implementation, rule documentation, definition of trigger criteria, and monitoring of control effectiveness.

Requirements

What you’ll need

Solid experience in Data Engineering, Data Analysis, or related fields.
Advanced knowledge of SQL and Python.
Experience with Databricks or similar data-processing platforms.
Experience building pipelines and integrating and processing data.
Experience with transactional monitoring and behavioral analysis.
Knowledge of REST APIs, log analysis, and event traceability.
Experience building automations, alerts, and monitoring mechanisms.
Knowledge of applied statistics, analytical modeling, and anomaly detection.
Ability to work autonomously in developing end-to-end solutions.
Experience investigating incidents, behavioral deviations, or operational risks.
Experience in Digital Fraud Prevention (preferred, but not required).
Experience in Cybersecurity or Information Security (preferred, but not required).
Knowledge of API protection and monitoring (preferred, but not required).
Experience detecting bots and automated attacks (preferred, but not required).
Knowledge of Machine Learning applied to anomaly identification (preferred, but not required).
Experience in payments, fintechs, banks, or financial institutions (preferred, but not required).
Experience with observability and monitoring tools such as Datadog, New Relic, Salt Security, Akamai API Security, Cloudflare API Shield, Wallarm, Cequence, or Imperva (preferred, but not required).

Benefits

Comp & perks

Transportation allowance or office parking
Meal allowance or food allowance — choose one of the two options
Health insurance
Dental insurance
Telemedicine — available 24 hours a day, every day of the week
Wellhub (formerly Gympass)
Zenklub
Work-from-home allowance
Profit-sharing bonus, in accordance with the applicable policy
Birthday day off — paid time off on your birthday and on the company’s anniversary
Sem Parar tag — provided at no cost
Life insurance
Parental leave — paid leave for mothers, fathers, or guardians to welcome a child through birth or adoption
Educational assistance — up to 25% off postgraduate programs or an MBA