AI Data Scientist at CREDIT AGRICOLE CORPORATE AND INVESTMENT BANK
Singapore, Southeast, Singapore -
Full Time


Start Date

Immediate

Expiry Date

25 Apr, 25

Salary

9000.0

Posted On

26 Jan, 25

Experience

10 year(s) or above

Remote Job

No

Telecommute

No

Sponsor Visa

No

Skills

Python, Analytical Skills, Information Technology, Kubernetes, Deep Learning, Machine Learning, Computer Science, Communication Skills, Mastery

Industry

Banking/Mortgage

Description

WHO WE ARE

Crédit Agricole Corporate and Investment Banking (Crédit Agricole CIB) is the corporate and investment banking arm of Crédit Agricole Group, world’s 12th largest bank by total assets.

  • Our Singapore center (“ISAP” or “Information Systems Asia Pacific”) is the 2nd largest IT setup (after Paris Head Office)” for Crédit Agricole CIB’s worldwide business. We work daily with international branches located in 30 markets by:
  • Envisioning and preparing the Bank’s futures information systems
  • Partnering and supporting core banking flagships and transverse areas in their large scale development projects.
  • Providing premium In-house Banking applications,
  • This unique positioning empowers us to bring our core banking business a sustainable competitive advantage on the market.
  • We seek innovative and agile people sharing our mindset to support ambitious and forthcoming technological challenges.

QUALIFICATIONS AND PROFILE

Experience required 10 years minimum in an IT functional architecture position or equivalent role

  • Expertise in machine learning, deep learning, generative AI and MLOps.
  • Knowledge of data management practices to clean, preprocess and transform data sets for model training
  • Mastery of AI algorithms and frameworks (e.g., Tensorflow, PyTorch, Scikit, etc.)
  • Knowledge of GEN AI and LLM technologies on the public Cloud using RAG patterns
  • Understanding the ethical principles to better generate embeddings for GenAI.
  • Expertise in Python, .NET or Java, DevOps / MLOps / LLMOps (GitLab CI/CD, Kubernetes, AWS Cloud

OTHER PROFESSIONAL SKILLS AND MINDSET

  • Excellent problem-solving and analytical skills.
  • Effective communication skills and ability to work collaboratively in a team.
  • Excellent Aptitude, Curious to learn and inquisitive.
  • Autonomous, self motivated and excellent team player.

EDUCATION REQUIREMENTS

At least a Bachelor’s degree in any of these faculties:

  • Computer Science
  • Information Technology
  • Programming & Systems Analysis
  • Science (Computer Studies)
Responsibilities

JOB RESPONSIBILITIES

  • Responsible for the design, development, maintenance of applications and systems as well as IT production and management of the Bank’s technical infrastructures.
  • At the forefront of technological innovation, its teams provide technical and functional support for the development activities and projects of the various Corporate and Investment Banking professions in an international environment.
  • Develop and implement advanced machine learning and deep learning models to automate and transform business processes in the capital markets value chain
  • Use and create data science models to produce strategic insights, develop sophisticated predictive models and deploy solutions meeting current standards.
  • Use generative AI models to create synthetic financial data, simulate market scenarios, generate new investment ideas, automate post-trade processes, and enrich seller interactions with relevant stakeholders.
  • Collaborate with quantitative analysts and traders to design solutions based on artificial intelligence.
  • Develop a product mindset on the exploitation of AI models to improve and build functional blocks in the IS ecosystem
  • Work closely with technical and business teams to resolve complex problems.
    Travel: Occasional

Experience required 10 years minimum in an IT functional architecture position or equivalent role

  • Expertise in machine learning, deep learning, generative AI and MLOps.
  • Knowledge of data management practices to clean, preprocess and transform data sets for model training
  • Mastery of AI algorithms and frameworks (e.g., Tensorflow, PyTorch, Scikit, etc.)
  • Knowledge of GEN AI and LLM technologies on the public Cloud using RAG patterns
  • Understanding the ethical principles to better generate embeddings for GenAI.
  • Expertise in Python, .NET or Java, DevOps / MLOps / LLMOps (GitLab CI/CD, Kubernetes, AWS Clou
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