DRW is a diversified, technology-led principal trading firm. We trade our own capital at our own risk, across a broad range of asset classes, instruments and strategies, in markets around the world. As the markets have evolved over the past 25 years, so has DRW – growing to include real estate, cryptocurrencies, venture capital and several industry acquisitions. With more than 800 employees at our Chicago headquarters and six global offices, we work together to solve interesting problems and capture opportunities. It’s a place of high expectations, deep curiosity, and constant collaboration, with some of the smartest, most passionate people you’ll meet.
Our Flow-Equity team is looking for a passionate, innovative Data Scientist to spearhead the efforts of creating an equity trading model using NLP techniques. As a member of this team, you have the opportunity to build a state-of-the-art and evolving trading strategy from inception to completion in a growth-oriented environment that champions disruptiveness and embraces failures on the way to success.
What you’ll be working on…
- Conducting cutting edge research to develop, implement, and perfect NLP algorithms for text/language/speech processing and sentiment analysis
- Applying quantitative techniques to large market datasets to obtain actionable insights and execute on them in real time
- Collaborating with internal Trade Execution, Data Acquisition, and Quantitative Research experts to build a next generation trading engine
- Building a world-class team of experts as required; striving to reach ambitious quantifiable long term goals, while presenting intermediate achievements
- Being a leading ML authority within the firm; staying at the forefront of the newest technologies, prototypes, and being proactive in ML communities
- Provide mentorship to your peers
You’ll feel right at home if you…
- Have 5+ years of applied experience in ML and NLP
- Preferably have experience in the financial industry with sound knowledge of investment concepts
- Have expert understanding of machine learning techniques; knowledge of packages such as Tensorflow, Pytorch, Keras, Scikit Learn, Mat-plotlib, XGBoost
- Have good knowledge of deep learning and more traditional machine learning algorithms
- Have experience with embeddings, transfer learning, and interpretability methods
- Have working knowledge of cloud computing such as AWS and Google Cloud
- Have the ability to build, validate, deploy and monitor iteratively advanced predictive models
- Have excellent scripting and programming skills (such as Python, SQL)
- Have experience in conducting ML/NLP projects
- Have a positive, team-focused attitude and strong collaboration skills
- Have excellent written and communication skills to present complete and cohesive findings
- Have the ability to produce clear, logical and convincing arguments and explain complex ideas simply
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