Our client, a leading global multi $ Bn hedge fund are now looking to hire a very talented trading quantitative researcher to join one of their expanding systematic teams.
This team focus on global equities using a data-driven and relative value approach. This is an excellent opportunity to support and learn from a very senior and successful PM which creates huge opportunity for career growth.
- Work alongside the PM on alpha research, with a primary focus on: idea generation, data gathering and research/analysis, model implementation and back testing for a systematic equity strategy focused on alternative and fundamental data
- Work on all stages of research, including meeting vendors, cleaning data, building models, back testing signals, and deploying to production
- Combine financial insights and statistical learning techniques to explore, analyze, and harness a large variety of datasets to build strong predictive models
- Collaborate with other team members in a transparent environment
- 3-5 years of experience in finance or technology, preferably working with alternative and fundamental data
- Experience using statistical techniques in prediction models and building systematic signals
- Experience with all or any of the following: big data, web scraping, data analysis and predictions, machine learning, risk & position management, trading, and compliance
- Mastery of a numerical programming language (Python, MATLAB, R, or Julia)
- Experience working with databases and cloud services (SQL, NoSQL, AWS)
- Highly competent in statistics and probability, with an emphasis on high-dimensional regression (e.g. lasso, elastic net) and time series forecasting (e.g. ARIMAX, Prophet)
- Bachelors, Masters or PhD degree in a quantitative subject such as Applied Mathematics, Statistics, Computer Science or related field from a top ranked university
- Experience working with large data sets (e.g. map reduce, EMR, Spark, etc.)
- Excellent communication, analytical and quantitative skills
Please get in touch or send your resume to: firstname.lastname@example.org to discuss further.