22 дня назад
Data Scientist (Banking Risk)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Scientist (Banking Risk) (AI and banking): Building statistical risk models, capital optimization frameworks, and regulatory solutions for treasury, wholesale banking, and corporate lending with an accent on PD, LGD, EAD, Basel requirements, and production-ready Python engineering. Focus on designing quantitative models, validating regulatory alignment, processing complex financial requirements, and presenting model methodologies to senior banking stakeholders.
Location: On-site in Dubai or Abu Dhabi, United Arab Emirates
Company
AI and data consultancy building bespoke intelligent systems and enterprise solutions, with particular expertise in financial services and banking.
What you will do
- Design and implement statistical risk models for corporate lending, wholesale banking, liquidity management, and treasury operations.
- Build Probability of Default, Loss Given Default, and Exposure at Default model architectures.
- Develop Risk-Adjusted Return on Capital and Risk-Adjusted Capital optimization frameworks.
- Apply Basel III/IV requirements, 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 explain quantitative findings and defend model methodologies.
Requirements
- Hands-on experience developing statistical risk models or quantitative frameworks in corporate banking, wholesale banking, or treasury.
- Strong theoretical and practical knowledge of quantitative, mathematical, and probabilistic concepts behind machine learning and statistical methods.
- Strong Python skills and experience with 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 complex statistical trade-offs to technical and business audiences.
- Bachelor’s or Master’s degree in Statistics, Mathematics, Data Science, Quantitative Finance, or a related quantitative discipline.
Nice to have
- Experience with experiments and causal analysis for high-stakes financial decisions.
- Familiarity with Transformers and sequence models for financial sentiment analysis and time-series forecasting.
- Experience with PySpark, Spark, or Dask on large-scale enterprise data lakes.
- Experience creating interactive data narratives and dashboards with Streamlit or Plotly.
Culture & Benefits
- Individual visa sponsorship.
- Comprehensive Gold Level personal health insurance.
- Professional development and certification support.
- Role-related subscription reimbursement.
- Monthly employee incentive program and career advancement opportunities.
- Opportunity to work on AI projects for regional financial-services clients.
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