Senior Data Analyst

Apache Spark

Java

PL/SQL

SQL

Apache Kafka

Microsoft Azure

C++

Machine Learning

Responsibilities:

• Proactively and dynamically develop complex data analyzes in order to identify patterns of suspicious financial crime activities, as well as support investigations;
• Analyze high volumes of data and information in order to define / calibrate financial crime prevention models, and test the effectiveness and efficiency of these models;
• Have the expertise and challenge skills necessary to request / articulate / coordinate with the Corporate Models team the need / requirements / selection of AI / ML / Others models that make sense and are an added value in PBC, and ensure good implementation;
• Ensuring, in conjunction with the rest of the PBC team, the recurrent applicability in BAU of new processes and models of tests or more intelligent and automatic lookback alerts;
• Identify, articulate and directly ensure with IT the need to provide additional data to better support the various analyzes and tests;
• Develop performance and risk indicators on financial crime prevention systems, as well as subsequent monitoring analyzes;
• Participate in development projects on monitoring systems and IT controls in direct contact with other areas of the Bank;
• Develop reports of conclusions and / or monitoring in a clear, logical and objective way.

• Solid knowledge in data exploration and treatment (ORACLE SQL and PL \ SQL, SPARKSQL, etc.)
• Knowledge of some object-oriented programming language (namely Java, C ++, etc.)
• Experience in cleaning and structuring data from various sources, including unstructured sources
• Familiarity with the construction of graphical representations of data, through descriptive statistics and correlations
  
• Ability to prepare data for modeling, namely treatment of missing values and outliers, based on their business meaning
• Knowledge or willingness to learn Big Data technologies and methodologies, namely in the Apache and Azure ecosystem
• Knowledge or willingness to learn streaming technologies (namely Kafka)
• Notions of statistical modeling and machine learning
• Creativity and critical thinking in the search, interpretation and transformation of data for non-trivial uses

• Family Friendly Enterprise Certification
• Great Place to Work Awards
• FlexiWorking
• Annual Leave is composed by:
  • 25 days;
  • Children Birthday;
  • Own Birthday;

• Gym in the Headquarters

To apply for this job you must be willing to work in the time zones between UTC+1 and UTC+1.