Advanced Analytics – Senior Data Scientist (H/F)
Banque Internationale à Luxembourg
Luxembourg, Luxembourg
il y a 1j
source : Dogfinance

Description

Banque Internationale à Luxembourg (BIL) is one of the largest banks in the Grand Duchy and offers retail, private, corporate and institutional banking as well as treasury and financial market services.

We are focused on Luxembourg and select international markets, and on a long-term value creation by empowered individuals and teams.

Most of BIL's 2000 employees work at the headquarters in Luxembourg city : the centralized setup promotes swift , agile decision-making and enabling BIL to offer clients innovative solutions for their changing needs.

Responsabilités

In order to accelerate BIL transformation and to enforce Advanced Analytics team, we are currently looking for a Senior Data Scientist.

Missions :

As a member of the Advanced Analytics team, you will apply statistical and quantitative approaches in a growing scope of applications, such as :

  • Commercial performance & marketing analysis
  • Risk monitoring automation
  • AML KYC / KYT compliance
  • Internal processes efficiency
  • Data quality improvement
  • And more globally, contribute to make BIL to become a data driven organization, by identifying proactively new business cases to tackle with Data Science.

    The transversal scope of Advanced Analytics team involves a collaboration with a wide range of BIL services and profiles.

    More than being a technical position, this role requires to understand business stakes and to be able to propose the best way to tackle problems (including new ones if needed).

    In consequence, a both business orientation and solution-oriented mindset is mandatory.

    As a data scientist, your day-to-day job will consist to :

  • Explore available data, to identify the best sources for models
  • Create new insights or new models, applying different statistical algorithms (supervised or non-supervised exercises) and choosing the most adapted to each business issue
  • Test model results, in close collaboration with sales forces and business supports, and deploy them for action when validated
  • Work closely with IT for industrialization, with BI Services for integration of data insights into reports, and Data Governance for enhancing Data Quality Management on Analytics outcomes
  • Leverage on Analytics Capabilities (Cluster Big Data with Spark) when it is relevant
  • Keep an observation activity about new methods, technologies, market trends in AI and Data Science (Machine Learning, Big Data, Deep Learning & Neural Networks, NLP ).
  • Contribute to the Lab (or R&D ) mindset of the team

    Profil recherché

    Exigences obligatoires

    Qualifications :

  • Strong statistical & mathematical background (e.g. ENSAI / ENSAE engineer)
  • 5 years of work experience, preferably as a data scientist or in highly technical and analytical role, within a financial institution (e.
  • g. Risk Management) or in a consulting firm

  • General knowledge of banking products. Knowledge of Marketing Analytics would be an asset.
  • Hands-on experience in working with large datasets / data warehouses, using data mining and modeling tools and languages (Python highly preferred)
  • Practical experience on Hadoop ecosystem (with Spark) would be an asset
  • Strong interest in new technologies, especially in Data Science & AI
  • In-depth knowledge on statistical modeling and predictive analytics (theory and practice) : Machine Learning, Deep Learning, NLP, image recognition
  • Strong communication and presentation skills to share findings and to explain complex statistical concepts to a non-technical audience
  • Profile :

  • Willing to combine a job with business and highly technical aspects
  • Knowledge in Business Intelligence tools & concepts (proven experience of an advanced Data visualization tool, such as Tableau or Qlikview, is an advantage)
  • Strong appetence for figures, statistics, algorithmic and quantitative activities
  • Client oriented, ability to understand business problems and appetence to have a real impact on them
  • Able to organize him / herself and set priorities
  • Willing to learn (technologies, methods) and to develop his own expertise
  • Team player
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