2 дня назад
Machine Learning Researcher (Fintech)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Machine Learning Researcher (Fintech) (Deep Learning/Time Series): Developing machine learning models and automation tools to enhance quantitative trading strategies, with an accent on deep learning, time series analysis, scalable deployment, and production implementation. Focus on designing experiments, extracting signals from complex financial datasets, and solving challenging market forecasting problems with researchers, engineers, and traders.
Location: Onsite in Bala Cynwyd (Philadelphia Area), Pennsylvania, United States
Company
is a global quantitative trading firm using machine learning, advanced quantitative research, and large financial datasets to develop systematic trading strategies.
What you will do
- Conduct research and develop machine learning models to improve trading strategies, focusing on deep learning and scalable deployment.
- Analyze forecasting problems involving time series, natural language understanding, and complex financial datasets.
- Design and run experiments with current machine learning tools and frameworks.
- Develop automation tools for research and system development.
- Extract signals from datasets and study market behavior using rigorous scientific methods.
- Collaborate with researchers, developers, traders, and engineering teams to implement and test models in production.
Requirements
- PhD in computer science, machine learning, mathematics, physics, statistics, or a related field.
- 5+ years of experience building impactful deep learning systems in academic or industry settings.
- Publication record in top-tier conferences such as NeurIPS, ICML, or ICLR.
- Strong programming skills in Python and/or C++.
- Practical experience with PyTorch or TensorFlow, particularly in production environments.
- Hands-on experience with deep learning for time series, plus strong foundations in mathematics, statistics, and algorithm design.
Culture & Benefits
- Immediate start opportunity.
- Intellectually driven and highly collaborative working environment.
- Close collaboration between researchers, engineers, and traders.
- Work focused on applying scientific research to real-world systematic trading challenges.
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