- Location
- Gurugram, Haryana, India
- Department
- Quantitative Trading
- Education
- PhD
- Source
- Greenhouse
Description
Who are we: Graviton is a privately funded quantitative trading firm striving for excellence in financial markets research. We trade across a multitude of asset classes and trading venues using a gamut of concepts and techniques ranging from time series analysis, filtering, classification, stochastic models, pattern recognition, to statistical inference analyzing terabytes of data to come up with ideas to identify pricing anomalies in financial markets.
As part of this team you will be tasked to apply machine learning and specifically deep learning techniques to trading problems while staying connected to broader research community. The researcher will put theory into practice and can immediately impact the global trading landscape with the expanding presence of Graviton in various markets.
Description
- Lead research in applying machine learning to a wide variety of datasets and trading problems
- Follow latest developments in academic research and incorporating research techniques from different fields of applications to our problems
- Improve tick-by-tick order book based time series feature sets using latest preprocessing techniques
- Work on current and develop new deep learning models to exploit large pool of in-house features and computing infrastructure
- Develop scalable pipeline for building predictive models across global markets
- Discover and implement new sources of predictive alpha, verify that they improve existing models, and integrate them into the firm's strategy development pipeline
- Partner with quant researchers and software developers in implementation of conducted research to production using Python / C++
- Advise infrastructure support team on latest developments on hardware and software to improve computing infrastructure for ML based research
Qualifications
- Masters or PhD in Computer Science, Mathematics, Statistics, or a related field
- At least two years of demonstrated experience of ML/AI research in a professional setting or at a reputable academic institution
- Track record of academic publications preferred
- Experience with software engineering in Python / C++
- Experience with Tensorflow, Keras, PyTorch is highly desirable
Benefits:
Our open and collaborative work culture gives you the freedom to innovate and experiment. Our cubicle free offices, non-hierarchical work culture and insistence to hire the very best creates a melting pot for great ideas and technological innovations. Everyone on the team is approachable, there is nothing better than working with friends!
Our perks have you covered.
- Competitive compensation
- Annual international team outing
- Fully covered commuting expenses
- Best-in-class health insurance
- Delightful catered breakfasts and lunches
- A well-stocked kitchen
- 4 week annual leaves along with market holidays
- Gym and sports club memberships
- Regular social events and clubs
- After work parties