Overview

BNP Paribas is a leading European bank with an international reach. It has a presence in 72 countries, with more than 202,000 Employees – including more than 154,000 in Europe and over 5,000 in Portugal alone.

BNP Paribas is present in Portugal since 1985, having been one of the first foreign banks to operate in the country. Today, BNP Paribas has several entities operating directly in this territory, offering a wide range of integrated financial solutions to support its clients and their businesses.

Worldwide, the Group has key positions in its three main activities: Domestic Markets and International Financial Services (whose retail-banking networks and financial services are covered by Retail Banking & Services) and Corporate & Institutional Banking, which serves two client franchises: corporate clients and institutional investors. The Group helps all its clients (individuals, community associations, entrepreneurs, SMEs, corporate and institutional clients) to realise their projects through solutions spanning financing, investment, savings and protection insurance.

The Team

CIB Analytics Consulting (AC) consists of 60 people based in Paris, and Lisbon. Reporting to the CIB Chief Data Officer, Analytics Consulting is an in-house center of expertise on Data, Analytics and Artificial Intelligence. It is at the forefront of the data transformation of BNP Paribas CIB and the team is constantly evolving. It helps internal entities (primarily CIB) better understand and use internal & external data. It offers dashboarding, advanced analytics capabilities and AI applications to its internal clients in response to their business needs.

Key Responsibilities
Manage End to End Product Lifecycle:
Collaborate with clients to understand their operational and strategic needs
Supervise the design, development and run of solutions, in collaboration with other internal and external stakeholders
Implement and assist the deployment and maintenance of models:
Follow to best practices in the industry to implement and scale out the developed solutions into production grade software
Assist the operational teams with the deployment, monitoring and maintenance of the developed solutions
Act as a bridge between the different practices of the team and other external stakeholders
Ensure Data/AI/App Dev are working in sync
Ensure all solutions components are dully developed, tested and rolled out amongst the different teams
Work closely with clients during all stages of the application life cycle
Design the most adequate approaches to solve the identified problems within the company’s framework
Lead and Advise the team on technical topics:
Act as a go to technical expert for the management of complex AI products
Contribute in establishing best practices for data science projects, over the full product lifecycle.
Guarantee the training of the team members and the internal compliance with the defined best practices.
Support End to End Product Lifecycle for BI activities
Ensure link is made between AI and BI initiatives
Contribute in the establishment of best practices and management of the BI stack
Participate in BI initiatives on demand
Contribute to disseminate a culture of data driven solutions within CIB
Maintain a strong market watch on the latest developments on methodologies, technologies and tools
Develop and share best practices with the Analytics Consulting team

Experience
7+ years of professional experience in similar functions
Experience in working in large and complex international groups
Experience in solving complex multi-dimensional problems
Experience in developing Machine Learning models
Experience in Web Applications development
Experience in Data driven initiatives and statistical analysis software
Experience in Team Management

Company:

BNP Paribas

Qualifications:

Technical skills
Ability to explain the results of a model and the different elements impacting it
High statistical and quantitative analysis skills (e.g. machine learning models, statistical models, Bayesian statistics, probability theory, time series analysis, …)
Ability to think abstractly and creatively
Knowledge of databases and associated tools (SQL and NoSQL)
Knowledge of ETL methods
Effective Programming skills (e.g. Python, R, Java, Go, Javascript) and algorithmic knowledge.
Knowledge of at least one ML development stack (e.g. Numpy, scikit-learn, keras, …)
Knowledge of NLP techniques.
Knowledge of deep learning architectures and frameworks (e.g. Torch, TensorFlow, …)
Knowledge of advanced reporting tools (Tableau, PowerBI, …)

Soft skills
Leadership and team management skills
Excellent communication and interpersonal skills
Flexibility: ability to work in a changing environment
Project management skills

Education
Engineer School/Master’s degree from university. Specialization in mathematics, statistics or data science would be a plus
Although not strictly required a PhD on data, engineering or related fields is a plus

Language requirements:

Languages
Fluent English
French and Portuguese are a plus

Educational level:

Master Degree

Level of experience (years):

Mid Career (2+ years of experience)

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