Mid-Level Data and Analytics Analyst, Fraud Prevention

Jobtailor

São Paulo

Presencial

BRL 180 000 - 300 000

Tempo integral

Há 3 dias

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Resumo da oferta

Jobtailor in São Paulo, Brazil, seeks a data analytics professional to strengthen the Fraud Prevention team’s data intelligence capabilities. You will transform large volumes of operational information into analyses, metrics, and automated processes.

Map, understand, and document databases and business rules, develop SQL queries, and use Python for data processing and automation. Build Tableau dashboards and advance fraud-related metrics and insights.

Qualificações

Bachelor’s degree in a quantitative field (e.g., Data Science, Statistics, CS, Engineering).
Experience in fraud prevention, diagnostics, investigation, or enforcement.
Strong experience in Data Analytics, BI, or data analysis applied to operations.
Advanced SQL skills for querying large datasets.
Practical knowledge of Python for analysis and automation.
Experience building and maintaining dashboards and management metrics.
Experience with process automation and/or RPA.
Knowledge of ETL processes, data integration, data quality, and validation.
Experience developing productivity, efficiency, SLA, capacity, or operational metrics.
Preferred: experience in banks, fintechs, financial institutions, payment processors, payment companies, or insurance companies.

Responsabilidades

Structure and strengthen the Fraud Prevention team’s data intelligence capabilities.
Transform large volumes of operational information into analyses, metrics, and automated processes.
Map, understand, and document databases, data sources, and business rules.
Develop SQL queries to extract, integrate, process, and validate large volumes of data.
Use Python for exploratory analysis, data processing, and automated routines.
Build and maintain Tableau dashboards, ensuring reliability, traceability, and timely updates.
Develop metrics for volume, productivity, operational capacity, SLA, analysis time, criticality, and complexity.
Establish weighted productivity measurement criteria based on the difficulty, risk, and effort involved in analyses.
Create strategic metrics on prevented losses, recovered or preserved amounts, litigation costs, and the effectiveness of initiatives.
Analyze incidents by product, channel, customer journey, transaction method, and classification, identifying patterns, trends, anomalies, and vulnerabilities.
Support root-cause analysis and recommendations for Fraud Prevention, Operational Risk, Product, Customer Service, and Legal teams.
Develop automation and RPA solutions to reduce manual activities and increase efficiency and security.
Provide cross-functional support to the Diagnostics and Certification and Investigation and Enforcement workstreams.
Document queries, automations, rules, metrics, and procedures.

Conhecimentos

Advanced SQL skills

Python for data processing

Data Analytics

Business Intelligence

Data Validation

Statistical Analysis

Process automation and RPA

Fraud prevention experience

Operational performance metrics

Formação académica

Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Information Systems, Engineering, Economics, Business Administration, or related field

Ferramentas

Tableau

SQL

Python

RPA Tools

Data Lakes

Descrição da oferta de emprego

Structure and strengthen the Fraud Prevention team’s data intelligence capabilities.
Transform large volumes of operational information into analyses, metrics, and automated processes.
Map, understand, and document databases, data sources, and business rules.
Develop SQL queries to extract, integrate, process, and validate large volumes of data.
Use Python for exploratory analysis, data processing, and automated routines.
Build and maintain Tableau dashboards, ensuring reliability, traceability, and timely updates.
Develop metrics for volume, productivity, operational capacity, SLA, analysis time, criticality, and complexity.
Establish weighted productivity measurement criteria based on the difficulty, risk, and effort involved in analyses.
Create strategic metrics on prevented losses, recovered or preserved amounts, litigation costs, and the effectiveness of initiatives.
Analyze incidents by product, channel, customer journey, transaction method, and classification, identifying patterns, trends, anomalies, and vulnerabilities.
Support root-cause analysis and recommendations for Fraud Prevention, Operational Risk, Product, Customer Service, and Legal teams.
Develop automation and RPA solutions to reduce manual activities and increase efficiency and security.
Provide cross-functional support to the Diagnostics and Certification and Investigation and Enforcement workstreams.
Document queries, automations, rules, metrics, and procedures.

Requirements

Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Information Systems, Engineering, Economics, Business Administration, or a related field.
Experience in fraud prevention, diagnostics, investigation, or enforcement.
Strong experience in Data Analytics, Business Intelligence, or data analysis applied to operations.
Advanced SQL skills for querying, joining, validating, and manipulating large datasets.
Practical knowledge of Python for analysis, data processing, and automation.
Experience building and maintaining dashboards and management metrics.
Experience with process automation and/or RPA.
Knowledge of ETL processes, data integration, data quality, and validation.
Experience developing productivity, efficiency, SLA, capacity, or operational performance metrics.
Preferred: experience in banks, fintechs, financial institutions, payment processors, payment companies, or insurance companies.
Preferred: knowledge of banking products and experience working with customer service, complaints, legal cases, risk, or financial operations data.
Preferred: advanced Tableau skills.
Preferred: experience with data lakes, data architecture, or high-volume, multi-source environments.

Core Competencies

Demonstrates expertise in Data Analytics and Business Intelligence, with strong capabilities in SQL and Python for data processing and automation. Proficient in developing metrics and dashboards to enhance operational performance and fraud prevention strategies.

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