OUR CLIENT is
A proprietary trading firm with offices in DC and AL. They bring a rigorous quantitative approach, supported by scalable technologies, to their investment decisions. Their current area of focus is wholesale power markets. They began transacting in 2013 and is a registered market participant in CAISO, ERCOT, MISO, SPP, and PJM.
THE QUANT ANALYST will
Join an amazing team of Quantitative Analysts and Developers where you will work closely and collaboratively with Trading and Technical teams with the ultimate goal of supporting day-to-day trading operations with your quantitative abilities. You will work daily with large amounts of real-time data to create predictive models, risk management methodologies, and optimizations on trading strategies. This position heavily involves R programming, data management (e.g. SQL, Cassandra, Redis), and working in production and R&D AWS cluster environments.
You will be expected to communicate your approach and findings clearly and concisely to other teams. You must be able to work in a dynamic, collaborative environment. It is important that you are enthusiastic about joining an early-stage company. You will need to be flexible, driven, collaborative, and comfortable juggling responsibilities in multiple disciplines.
- Evaluate and build various models used by our trading and risk management teams.
- Regularly evaluate forecasting models and optimizations results created by our teams and external vendors. Provide visualizations and reports of your findings.
- Assist in the creation, maintenance, and enhancement of predictive models and optimization systems to enhance trading performance.
- Collaborate with other teams to develop, test, and optimize current and new trading strategies based on patterns detected by data analytics.
- Collaborate with other teams to turn experimental models into production-ready systems.
JOB EXPERIENCE REQUIRED
- Entry level/junior Quantitative Analyst position.
- Excellent quantitative problem solving skills are required.
- An excellent foundation of quantitative theory coupled with an ability to build real-world models and analytical tools.
- Driven, organized, and able to work on independent research and real-world problem solving with efficiency and accuracy.
- Solid experience and skill in quantitative programming (for example R, MATLAB, SAS, S-Plus). Strong proficiency in R and SQL. Experience with other database technologies (e.g. Redis, Cassandra, DynamoDB) is a plus.
- Expertise in predictive modeling, data mining, machine learning, and optimization.
- Experience with distributed computing and big data systems (Hadoop, Spark, etc) is a plus.
- Eagerness and ability to learn new technologies and programming languages quickly.
- Good communication skills to explain and justify your conclusions to non-technical stakeholders.
- BS in a quantitative discipline (e.g. Math, Computer Science, Engineering). Further education or work experience in a quantitative discipline is preferred.
- Coursework or equivalent experience must include Probability and Statistics, Stochastics, Regressions, Mathematical Optimizations/Linear Programming, Data Mining/Machine Learning.