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candidaturas
IT Developer/ Data Analyst
de BNP Paribas Lisboa em Lisboa (Publicado em 19-01-2021)
BNP Paribas is a leader in the Eurozone, and a prominent international banking institution with strong roots in Europe's banking history. It has a presence in 71 countries, with 200 000 Employees ? including more than 150 000 in Europe and 6 000 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, the Group has several entities operating directly in this territory, offering a wide range of integrated financial solutions to support its clients and their businesses.
Thanks to its international presence and regular and close collaboration among its businesses, BNP Paribas has the resources to support all clients - individuals, entrepreneurs, SMEs, large corporates, institutional investors and community organisations - with financing, investment, savings and protection solutions that help make their projects a success. BNP Paribas holds key positions in its three core operating divisions: Domestic Markets and International Financial Services for retail banking and specialised financial services, and Corporate & Institutional Banking for corporate and institutional clients.
BNP PARIBAS Group Finance, RISK, and ALM Treasury, have set-up a shared team in charge of the Group stress testing, the financial planning and the financial synthesis.
The team named STFS, for Stress Testing and Financial Synthesis, has for objective to coordinate the strengthening of BNP Paribas? Stress-Testing (S/T) and planning capabilities so as to better serve Business Lines, Legal Entities and Group needs and meet supervisory requirement on these matters, and in a cost-efficient manner.
To that effect, STFS aims at building a flexible, industrialized, central utility accessible by BNP Paribas? Business Lines and Entities (B/E) for their local needs and their contribution to Group exercises. STFS offers an integrated S/T service to B/Es to support them in capitalizing on the shared framework for their local needs.
STFS is also responsible for executing all Group-wide, comprehensive stress testing exercises, whether regulatory or internal.
STFS supports B/E?s S/T initiatives to ensure consistency with group standards while respecting local regulatory and supervisory requests.
Within the STFS platform, Stress-Testing Data Analytics (STDA) is the STFS data model owner for the S/T platform, and provides STFS with the data necessary for modelling activities and S/T exercises.
STDA develops Datamarts for Stress Testing on the RISK & Finance shared Big Data platform
In addition to data crushing and data analysis, STDA works jointly with IT Group on the automation of data ingestion, code processing, and data visualization processes. The team is the entry point of IT Group concerning data navigation and statistical exploration (DATAIKU) as well as data visualization (TABLEAU)
STDA serves other STFS teams with statistical analyses based on historical data
STDA is in charge of the monitoring of the data quality
The STDA team in Lisbon is dedicated to credit and works in a one-team manner with the STDA team based in Paris
ROLE AND RESPONSIBILITIES
The team is looking for a data analyst, also the primary focus will be on the development, maintenance and testing of STDA datamarts in a Big Data environment
The objective is to set up Datamarts for STFS to be able to stress capital and cost of risk on the credit risk perimeter of the bank. This includes the following processes:
Data ingestion, Data quality, Data preparation with DATAIKU DSS (Data Science Studio)
Data visualization with TABLEAU
Specific contributions to regulatory and internal stress testing exercises
Within this role you'll be able to:
Develop understanding of Stress Testing exercises
Have an exhaustive view on BNP PARIBAS credit risk perimeter
Learn all the fundamentals of credit risk data and measurement (RWA and Expected loss calculations)
Learn and develop programming skills and knowledge in a big data environment (PYTHON, PYSPARK, HIVE QL)
PROFILE
To be successful in this role, the candidate should meet the following requirements:
Appetite for the credit data functional content and understanding of stress tests modelling team requirements are a must.
Junior (0-3 years experiences - willingness to consider recent graduates) with strong desire to learn
Strong academic background, with a Master degree
Skills: significant experience in data exploration and data preparation. Good knowledge of SQL. Experience with PYTHON programming language is a plus.
Knowledge of Risk Management principles is a plus.
Languages: fluent in English
Strong interest in data management and functional content of the data
Ability to work with tight deadlines and multidisciplinary teams
Be a team player
Open and client-oriented mindset
Autonomy & Adaptability
Strong curiosity
Result oriented
Ability to communicate and share
This role will expose the candidate to a wide range of Risk and Finance professionals within the bank. Therefore, communication skills, both written and verbal, play an essential part in the day-to-day role.
Very strong ethics standards
The candidate should be available for periodic training abroad (short term in Paris).
Please note that only applications submitted in English will be considered.
In case you are selected for this role, further documentation will be requested to support your hiring process.
BNP Paribas is an equal opportunity employer and proud to provide equal employment opportunity to all job seekers. We are actively committed to ensuring that no individual is discriminated against on the grounds of age, disability, gender reassignment, marriage or civil partnership status, pregnancy and maternity, race, religion or belief, sex or sexual orientation. Equity and diversity are at the core of our recruitment policy because we believe that they foster creativity and efficiency, which in turn increase performance and productivity. We strive to reflect the society we live in, while keeping with the image of our clients.
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