Location: New York, USA
Most of the world’s digital information was created in the last few years with the vast majority of that information being unstructured in the form of text, tweets, videos, images, blogs, etc. The rate of growth of digital information vastly exceeds our biological processing abilities. The consequence for investors is that it’s becoming harder to make sense of the factors that drive financial markets. Acting upon partial understanding of vast quantities of information (i.e., heuristics) infuses investment decisions with cognitive biases. In order to beat markets and make money, humans need to augment their reasoning capacity, consider the relevance of more information, and make bias-free decisions.
At Accrete.AI, our vision is to help investors generate alpha, or excess returns, by training machines to think in the language of the markets. We leverage deep learning and Machine Augmented Collective Intelligence (MACI) to train machines to reason and learn so they can help human investors make better investment decisions.
- Two to three years of experience with Artificial Intelligence, Quantitative and Qualitative Analytics, Deep Learning, Machine Learning, Natural Language processing and Unstructured data analytics
- Good knowledge of machine learning techniques, feed-forward, recurrent and convolutional neural networks, entropy models, supervised and unsupervised learning
- Experience with one of the following: Theano, Tensorflow, Caffe, or any other deep learning/machine learning framework
- Strong willingness and aptitude for learning new concepts and analytical approaches
- Ability to formulate hypotheses, draw conclusions and deliver results
- Experience working with datasets, and strong interest in deep data analysis – you need to be a detective at heart.
- Effective interpersonal communication skills
- Must have at least a Master’s degree or PhD, preferably in Applied Mathematics, Computer Science, Statistics or Economics
- Work with deep learning models optimize/customize/refine them
- Define and design corpus structures, ANNs, and required activation functions
- Document use cases and develop component and Interaction (sequence) diagrams
- Design, development and delivery of tested code in an innovative, and, evolutionary environment.
- Work effectively in teams, managing and leading teams
- Provide effective, constructive feedback to the delivery leader
- Manage client expectations and work with an agile mindset with machine learning and AI technology