4 дня назад
Machine Learning Engineer Intern (Fintech)
1 500€
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Machine Learning Engineer Intern (Fintech): Developing an interactive dashboard to compute the profitability and assigned risk of a finance product with an accent on machine learning, data analysis, and model lifecycle implementation. Focus on building data-driven tools, supporting model training and deployment, and integrating robust Python code with CI/CD and DevOps practices.
Location: Milan, Italy — hybrid
Compensation: €1,500/month
Company
applies advanced analytics across banking functions including business, risk, retail, and corporate banking.
What you will do
- Develop an interactive dashboard for computing the profitability and assigned risk of a finance product.
- Build and maintain a codebase supporting the creation of machine learning models.
- Train, deploy, and monitor machine learning models for business needs.
- Conduct ad hoc data analyses and develop dashboards and tools that improve data accessibility.
- Work across the lifecycle of analytics solutions, from initial design through implementation.
Requirements
- At least 2 years of practical experience with Python or a similar programming language.
- Knowledge of object-oriented programming and Git workflows.
- Experience with CI/CD pipelines and DevOps practices.
- Strong data handling skills.
- Fluent written and spoken English.
- Strong communication, collaboration, self-direction, and ability to perform under pressure.
Nice to have
- Public projects on GitHub, Azure, or similar platforms.
- Familiarity with machine learning libraries and frameworks such as scikit-learn.
- Experience with credit decision models, business models such as churn or propensity, or clustering techniques.
Culture & Benefits
- Hybrid work in Milan.
- Opportunity for students to write a thesis on the finance-product dashboard topic.
- Collaboration with stakeholders across multiple banking areas.
- Work involving high ethical standards, honesty, and integrity.
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