Machine Learning Researcher

Role Overview: You will be leading research in applying machine learning to a wide variety of datasets and trading problems at Graviton, a privately funded quantitative trading firm. Your role will involve staying updated with the latest developments in academic research and incorporating research techniques from different fields of applications to solve trading problems. Additionally, you will work on improving tick-by-tick order book based time series feature sets, developing new deep learning models, and building a scalable pipeline for predictive models across global markets. Key Responsibilities: - Lead research in applying machine learning to various datasets and trading problems - Stay updated with the latest developments in academic research and incorporate research techniques from different fields - Improve tick-by-tick order book based time series feature sets using latest preprocessing techniques - Develop new deep learning models to exploit in-house features and computing infrastructure - Create a scalable pipeline for building predictive models across global markets - Discover and implement new sources of predictive alpha and integrate them into the firm's strategy development pipeline - Collaborate with quant researchers and software developers to implement research using Python / C++ - Advise the infrastructure support team on the latest developments in hardware and software for ML-based research Qualifications Required: - 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 (Additional details of the company have been omitted from the Job Description) Role Overview: You will be leading research in applying machine learning to a wide variety of datasets and trading problems at Graviton, a privately funded quantitative trading firm. Your role will involve staying updated with the latest developments in academic research and incorporating research techniques from different fields of applications to solve trading problems. Additionally, you will work on improving tick-by-tick order book based time series feature sets, developing new deep learning models, and building a scalable pipeline for predictive models across global markets. Key Responsibilities: - Lead research in applying machine learning to various datasets and trading problems - Stay updated with the latest developments in academic research and incorporate research techniques from different fields - Improve tick-by-tick order book based time series feature sets using latest preprocessing techniques - Develop new deep learning models to exploit in-house features and computing infrastructure - Create a scalable pipeline for building predictive models across global markets - Discover and implement new sources of predictive alpha and integrate them into the firm's strategy development pipeline - Collaborate with quant researchers and software developers to implement research using Python / C++ - Advise the infrastructure support team on the latest developments in hardware and software for ML-based research Qualifications Required: - 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 (Additional details of the company have been omitted from the Job Description)