Data Scientist – Scoring Center (M/F)

BNP Paribas Personal Finance

Lisboa

Híbrido

EUR 50 000 - 75 000

Tempo integral

14 dias+

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Vantagens oferecidas por esta oferta de emprego

Innovative team environment
On-the-job training
Networking opportunities

Resumo da oferta

A leading consumer finance company in Lisbon seeks a Data Scientist for the Scoring Center. The role involves building risk prediction models, leading projects, and conducting statistical studies. Candidates should possess a degree in Data Science, at least 3 years of experience in risk or statistical environments, and strong skills in Python. The company offers an inclusive culture and a hybrid work environment, encouraging innovation and teamwork.

Qualificações

  • Minimum 3 years experience in a statistical or risk environment, preferably in banking or insurance.
  • Good skills in Python and modelling environment.
  • Fluent in oral and written English.
  • Proficient with modelling environments or Data Lab and main data science libraries.
  • Experience with machine learning models industrialization.
  • Ability to manage multiple projects in parallel with accuracy.
  • Fluent in written and spoken English.

Responsabilidades

  • Build risk prediction models and lead projects.
  • Monitor and optimize score models.
  • Conduct statistical studies related to risk prediction.
  • Conduct statistical studies and support Basel regulatory projects.
  • Contribute to transversal Scoring Center activities: watch, training, and international support.

Conhecimentos

Python
Statistical Analysis
Risk Modelling
Machine Learning
Data Science Libraries
Risk Modelling

Formação académica

Degree in Data Science, Mathematics or Statistics

Ferramentas

DataLab

Descrição da oferta de emprego

Present in more than 30 countries, BNP Paribas Personal Finance leads the personal and consumer credit business. In some markets we are leaders, and we bet on innovation to open up new opportunities, in others we are a fast growing business. In all markets, we value relationships, knowledge sharing and responsible action.

In practice, your day-to-day
  • As a Data Scientist in the Scoring Center team, you will undertake projects to build risk prediction models. Your main responsibilities will be:
    • As part of your modelling projects, you assess the needs expressed, define and propose the adapted deliverables and estimate their burden and time frame through an implementation plan that takes into account the challenges and constraints. You use statistical modelling methods (such as Logistic Regression, Random Forest, Gradient Boosting…), analyze and explain the results
    • You lead the project, keep track of the schedule and support the implementation and monitoring of the tools issued
    • As part of the monitoring and optimization of the BNP Paribas Personal Finance score models, you participate in the monitoring campaigns of the scores: generation and analysis of monitoring results, diagnosis and action plan
    • You are also responsible for conducting or analyzing statistical studies related to risk prediction models. If necessary, you take part in analytical support missions to the Group's international entities and in the processing of audit recommendations relating to the Basel regulatory project
    • In addition, you actively contribute to the transversal missions of the Scoring Center: technological and methodological watch, regulatory watch, training, analytical support for the Group's international entities
The Mission is important, but so is the Team and the workplace!
  • Welcome to BNP Paribas Personal Finance, where you will integrate the Analytics Hub, an innovative, international and creative team. Our working language is English
  • You will be in the Scoring Center teams that are made up of 30 Data Scientists that will work with you. The team in Lisbon is new and everyone is growing together. You'll be surrounded by colleagues working in the same field as you, sharing ideas and experiences
  • We are prepared to welcome you with an initial onboarding plan, with on-the-job training, online learning and networking opportunities
What do we have to offer you?
  • This is a very important topic that we will address together, taking into account your training and experience.
Are you the one we are looking for?
  • Do you have a Degree in Data Science, Mathematics or Statistics?
  • Do you have a scientific background and at least 3 years of experience in a statistical or risk environment, preferably modelling in banking or insurance environment?
  • Do you have good skills in Python?
  • Are you proficient in modelling environment or data lab and have a strong knowledge of the main data science libraries?
  • Do you have experience in machine models industrialization?
  • Are you able to work on several projects in parallel and are acknowledge for your accuracy?
  • Are you fluent in oral and written English?
  • If you recognize yourself in this description, and have a lot of enthusiasm, energy and motivation, then you are the one we are looking for!
  • We look forward to your application!
Our commitments
  • BNP Paribas is an equal opportunity employer that is proud to provide equal employment opportunities to all job seekers. As a socially responsible company, we incorporate the principles of Diversity and Inclusion in our values and practices
  • To achieve all our goals, we intend to attract, develop, and retain different profiles, assuming diversity as an enabler and differentiator of innovation, fundamental in our organization
What makes us proud as reference employer?
  • Top Employer Portugal and Top Employer Europe certification, for the seventh consecutive year
  • 92% of our employees identify BNP Paribas as a company with "an inclusive management that supports all kinds of differences (age, origins, sexual orientation ...)"
  • 93% of employees identify with and benefit from the "Smart Working" policy, feeling comfortable in a hybrid work environment, and with the digital tools and workspaces available
  • 71% of our customers are promoters of our brand
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