Held by the Crédit Agricole Group, one of the largest European banking groups, Banco Credibom operates in consumer credit and is the leader in automobile financing.
Present in Portugal since ****, it provides personalized advice to customers and partners with flexible, transparent credit solutions adapted to their needs.
Mission:
Be part of theModelling and Innovationarea within theCredit Department, boostinganalytic powerfor client's profiling within credit acceptance, recovery in collections, fraud prevention and also to participate oninnovative projectslikeOpen Banking,Green financingorYounger people, and globally investigating new ideas or developingGenerative AIuse cases.
Qualifications:
Graduate from STEM degree (@science, @technology, @engineering or @maths);
Expertize usingSQL databases (bonus for experience with operational and data warehouse systems);
Expertize usingstatistical computer languages (Python, R, etc.) to manipulate data and specially to drawadded valueinsights from large data sets;
Knowledge of a variety of machine learning techniques and advanced statistical techniques (factor analysis, clustering, decision tree learning, xgboost, artificial neural networks, regression, properties of distributions, statistical tests);
Experience visualizing/presenting data for stakeholders using python mathplot lib, shiny server in R or PBI;
Experience on Data Architecture and/or Cloud tools;
Experience automating tasks in production environments;
Will be well valued:
Knowledge, or better yet, real experience withOpen Bankingenvironments, data categorization or use within credit acceptance or know-our-customer policies;
Knowledge of Credit risk in the banking industry (Scorecards, Acceptance workflows, Cost of risk, Risk based Pricing)
Experience with Machine Learning operations and understanding of the deployment process intorealproduction of those models
Knowledge of Apache Hadoop and Apache Spark
What to expect challenges and daily routines:
Build, test, and maintain database pipeline architectures, machine learning models or decision-based systems;
Develop algorithms to transform data into useful, actionable information;
Developprocesses and tools to monitor evolution and evaluate performance and data accuracy of models;
Use predictive modelling to improve credit risk at new production or at outstanding portfolio;
Developthe Open Banking capabilities to improve credit risk modelling
Location:
Lisbon (preferably) or Porto office, mixed with Teleworking 3 to 4 days a week.
Immediate availability.
Temporary replacement contract due to maternity leave (mandatory).
At Banco Credibom, we are inclusive.
We promote equality and respect for diversity in all areas of the company, encouraging tolerance and well-being for everyone.
For this reason, all candidates who participate in our recruitment processes are evaluated based on their experience and skills, without considering criteria that could create any type of discrimination, such as gender, age, race, religion, among others.