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Senior Quant Researcher | High Frequency Delta 1 - Expression of Interest
Привлекательная позиция в ведущей проп-трейдинговой компании с штаб-квартирой в Гонконге. Предлагает работу над сложными задачами, плоскую структуру управления и прямой вклад в финансовый результат, что обычно подразумевает высокие бонусы.
Сложность вакансии
Высокая сложность обусловлена требованиями к ученой степени (Masters/PhD), глубоким знаниям HFT (High Frequency Trading) и опыту написания продакшн-кода на C++. Работа в проп-трейдинге требует исключительных навыков в математике и анализе временных рядов.
Анализ зарплаты
Для позиции Senior Quant Researcher в Гонконге рыночный диапазон составляет от 1.2 до 2.0 млн HKD в год (базовая часть), не считая значительных дискреционных бонусов, которые могут удваивать доход. Данная вакансия соответствует топовому сегменту рынка.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Quant Researcher position at Eclipse Trading. With over five years of experience in quantitative research and a deep specialization in high-frequency Delta 1 strategies, I have a proven track record of developing predictive signals from massive time-series datasets. My background in C++ and Python, combined with a PhD in a quantitative discipline, aligns perfectly with your team's focus on low-latency trading and algorithmic innovation.
Throughout my career, I have successfully taken trading ideas from inception through rigorous backtesting to production release. I am particularly drawn to Eclipse Trading’s flat management structure and the opportunity to work directly where decisions are made in the Hong Kong headquarters. I am confident that my expertise in machine learning for sequence forecasting and my experience with real-time systems will allow me to make an immediate contribution to your Delta 1 and ETF trading desks.
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Откликнитесь в eclipsetrading уже сейчас
Присоединяйтесь к лидерам алгоритмической торговли в Гонконге и превращайте сложные данные в прибыльные стратегии!
Описание вакансии
Senior Quant Researcher | High Frequency Delta 1
Eclipse Trading is a leading proprietary trading firm. Founded in 2007, we have over 110 employees across 4 office locations – Hong Kong (our HQ), Sydney, Shanghai and Chicago. Our trading expertise and strategies are deployed across several markets globally, focusing on various products including equity derivatives, delta one, ETFs, commodity derivatives, and cryptocurrency. Technology is inextricably linked to our trading strategies, creating an environment powered by intellectual curiosity, problem solving, and innovation.
At Eclipse, we process hundreds of millions of data points per day, and the size and variety of data always grows. Our quantitative research team is based in our headquarters in Hong Kong, working where the decisions are made and have an opportunity to contribute directly to the bottom line.
The successful candidate will use our large amounts of internally and externally generated time series data and convert these to signals that help drive our trading and algorithms. The initial focus will be on predicting stock and futures short term moves.
Responsibilities and Duties
- Process and analyse large datasets to detect hidden signals and patterns in order to predict future events
- Perform quantitative analysis and modelling on the market to improve current trading strategies and develop new ones
- Take an idea from inception, through to detailed research, coding, and testing, and ultimately to production release
- Work independently yet closely with traders and IT staff
What you offer
- Masters or PhD in a quantitative discipline e.g. Statistics, Physics, Mathematics, Signal Processing, Machine Learning, etc
- 5+ years experience in analysing real world data in a first class research environment. Exposure to a variety of datasets would be an advantage. Experience in using machine learning to forecast sequence or time series data preferred
- 3+ years of financial markets experience working directly with trading desks
- Experience in high frequency Delta 1 trading, in equities or futures, preferred
- Experience working with low latency, real time systems preferred
- Very strong skills in writing production code in an OO programming language (prefer C++), and a statistical language (prefer Python), with understanding of software development workflows required
- Excellent communication skills
- Good command of spoken and written English
What we offer
- Dynamic and collaborative work environment
- A flat management structure, where everyone's voice is valued
- Work life balance within a multi-cultural environment
- Fully stocked kitchen for breakfast and lunch
- Attractive benefits package with discretionary bonus
Eclipse Trading is an equal opportunity employer and we believe that diversity and inclusion are essential pillars of our success as a company. We are dedicated to embrace a culture reflecting a variety of perspectives, insights and backgrounds to drive innovation. We build talented and diverse teams to drive business results and encourage our people to develop to their full potential.
All information provided will be treated in strict confidence and used solely for recruitment purposes.
Due to the high number of responses that we receive, we are only able to respond to successful applicants.
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Навыки
- C++
- Python
- Machine Learning
- Statistics
- Quantitative Analysis
- Time Series Analysis
- High-Frequency Trading
- Delta 1
- Signal Processing
- Algorithms
Возможные вопросы на собеседовании
Проверка понимания специфики HFT и работы с рыночными данными.
Как вы справляетесь с проблемой переобучения (overfitting) при разработке сигналов на высокочастотных данных?
Оценка технических навыков программирования для торговых систем.
Опишите ваш опыт оптимизации C++ кода для систем с низкой задержкой (low latency).
Проверка знаний в области Delta 1 и арбитража.
Какие основные факторы влияют на микроструктуру рынка при торговле Delta 1 продуктами (ETF, фьючерсы)?
Оценка навыков работы с данными.
Расскажите о наиболее сложном наборе данных, с которым вы работали. Как вы очищали данные и какие признаки (features) оказались наиболее значимыми?
Проверка способности доводить идеи до реализации.
Опишите процесс перевода исследовательской модели из Python в продакшн-среду на C++. С какими трудностями вы сталкивались?
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