Data Scientist
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Role Overview
DeepLight AI is seeking a Data Scientist with deep banking domain awareness to design, develop, and deploy statistical models and data-driven solutions.
The role works across Treasury, Wholesale Banking, and Corporate Lending to build risk models, portfolio optimization frameworks, and regulatory capital solutions.
Key Skills for This Role
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Company Overview
DeepLight AI is an AI and data consultancy delivering bespoke intelligent systems, statistical modeling, workflow automation, and systems integration.
The company focuses particularly on financial services and banking, building secure and scalable solutions for enterprise architectures.
The Opportunity
DeepLight AI is seeking a Data Scientist with deep banking domain awareness to design, develop, and deploy statistical models and data-driven solutions.
The role works across Treasury, Wholesale Banking, and Corporate Lending to build risk models, portfolio optimization frameworks, and regulatory capital solutions.
Responsibilities
- Design statistical risk models for corporate lending, wholesale banking, liquidity management, and treasury operations, including PD, LGD, and EAD architectures.
- Build RAROC and RAC optimization modules to help business lines maximize risk-adjusted returns.
- Apply Basel III/IV, stress-testing frameworks, and regulatory capital rules to model designs.
- Write modular, documented Python code and participate in peer code reviews.
- Collaborate with risk officers, business analysts, and technical leads to define requirements and present quantitative findings.
Required Qualifications
- Experience developing statistical risk models or quantitative frameworks within corporate banking, wholesale banking, or treasury environments.
- Strong understanding of quantitative, mathematical, and probabilistic concepts underlying machine learning and statistical tools.
- Strong proficiency in Python and scientific computing tools including NumPy, SciPy, Pandas, Scikit-learn, Statsmodels, and PyTorch or TensorFlow.
- Working knowledge of Basel III/IV, regulatory capital calculations, and banking stress testing.
- Strong analytical problem-solving, attention to detail, and ability to explain statistical trade-offs clearly.
- Bachelor’s or Master’s degree in Statistics, Mathematics, Data Science, Quantitative Finance, or a related quantitative discipline.
Preferred Qualifications
- Experience with experiments and causal analysis for high-stakes financial decisions.
- Familiarity with Transformers and sequence models for financial sentiment analysis or time-series forecasting.
- Experience with PySpark, Spark, or Dask on petabyte-scale enterprise data lakes.
- Experience creating interactive data narratives and dashboards with Streamlit or Plotly.
Benefits
- Competitive salary and comprehensive Gold Level personal health insurance.
- Individual visa sponsorship and professional development and certification support.
- Role-related subscription reimbursement, a monthly employee incentive program, and career advancement opportunities.
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