3 дня назад
Machine Learning Engineer Intern (Finance)
1 500€
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Machine Learning Engineer Intern (Finance): Building an interactive dashboard to compute the profitability and assigned risk of a finance product, while supporting machine learning model development across the bank with an accent on Python, data handling, and model lifecycle work. Focus on training, deploying, and monitoring models, developing data-access tools, and solving business and risk analysis problems.
Location: Milan, Italy (hybrid)
Salary: €1,500 per month
Company
is a bank organization apply advanced analytics and machine learn across business, risk, retail, and corporate bank.
What you will do
- Build and maintain a robust codebase support machine learn model creation.
- Train, deploy, and monitor machine learn models for different business needs.
- Develop an interactive dashboard for calculat the profitability and assigned risk of a finance product.
- Conduct ad hoc data analyses and develop tools that improve data accessibility.
- Collaborate with stakeholders across business, risk, retail, and corporate bank.
Requirements
- At least 2 years of practical experience with Python or a similar programm language.
- Knowledge of object-oriented programm and Git workflows.
- Experience with CI/CD pipelines and DevOps practices.
- Solid data-handl skills.
- Fluent written and spoken English required.
- Strong communication skills and the ability to work independently and collaboratively.
Nice to have
- Personal public projects on GitHub, Azure, or similar platforms.
- Familiarity with machine learn libraries and frameworks such as scikit-learn.
- Experience with credit decision models, business models such as churn or propensity models, or cluster techniques.
Culture & Benefits
- Hybrid work arrangement in Milan.
- Inclusive environment support diversity, equity, inclusion, and professional development.
- Opportunity to develop a thesis on the finance-product profitability and risk dashboard.
- Work with stakeholders across multiple areas of bank.
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