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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.
The Department
Capital Markets IT (CMI) is the IT department within the bank focused on solutions related to Capital Markets. Capital Markets IT involves technology solutions and systems used in financial markets for trading, investment, and related activities. This includes electronic trading platforms, risk management systems, market risk, counterparty risk, algorithmic trading, data analytics, and Regulatory measures. The use of advanced technologies like cloud and artificial intelligence is also becoming increasingly prevalent in capital markets to enhance efficiency and decision-making processes.
Team and Position
We are seeking a talented Data Scientist to join our dynamic Capital Market Department. This is a Contract role ONLY.
As an Data Scientist, you will be responsible for participate in development, training, deployment and management of data quality monitoring models using ML and GenAI. The person should be an experienced data scientist and shall also have the mindset to keep improvement of the model development process. You will work autonomously and follow a continuous improvement approach, ensuring high-quality code that adheres to our design, norms, and standards. You will be accountable for delivering solutions that meet both functional and non-functional requirements, taking into account the principles of Agile development.
Main Responsibilities
Qualifications and Profile
Technical
Functional
Nice to Have
Other Professional Skills and Mindset
For fair employment practices, we are keen on Singaporeans ONLY. We offer a competitive remuneration package, consistent with qualifications and experience.
Interested applicants, please click on 'APPLY'
Visit us on: http://www.ca-cib.com/
Job ID: 106885955
Skills:
Statistical Analysis, Tensorflow, Pytorch, Data Visualization, XGBoost, Machine Learning, Seaborn, Python, Plotly, LightGBM, Scikit-learn, Software engineering best practices, Deep learning frameworks
Skills:
geospatial data , Algorithms, Machine Learning, Apis, Time Series, Tensorflow, Pandas, Pytorch, XGBoost, Clustering, Containers, Python, scikit-learn, real-time analytics platforms, Linear Programming, reinforcement learning, Classification, Regression, Optimization Techniques, heuristics, Statistics
Skills:
data engineering , snowflake , MLops, Databricks, Python, Sql, Visualization, anomaly detection, Decision Intelligence, Time-Series Analysis
Skills:
Shell, Tableau, Python, Sql, risk management, Modeling, Analytics, R, Looker
Skills:
Microservices, Unix Shell Scripting, Numpy, Aws Ec2, Gitlab, Python, Sql, Jenkins, Pandas, DevOps methodologies, Prompt engineering, scikit-learn, Safety frameworks, Semantic search systems, Hugging Face, Bias mitigation, Diffusion models, LangChain, LLMs, Vector databases, Server-side APIs, In-context learning, Responsible AI, LlamaIndex, Transformer architectures, Model evaluation
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