As a Junior Quantitative Analyst you will work under the guidance of our Lead Quant. 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 assist in the creation of 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. As a Junior analyst, you will begin by playing a supportive role in various projects. As you skills and experience grows, you will take on increasing project responsibilities.
You will be expected to communicate your approach and findings clearly and concisely to other Tios Capital teams. You must be able to work in a dynamic, collaborative environment. It is important that you are enthusiastic about joining a small but highly productive company that is maturing from a start-up into best practices. You will need to be flexible, driven, collaborative, and comfortable juggling responsibilities in multiple disciplines.
This position is based in our Alexandria, VA office. You will be expected to travel to our Birmingham, AL office periodically (estimated 2-4 weeks of travel annually).
Assist with efforts to develop, test, and optimize current and new trading strategies based on patterns detected by data analytics.
Assist with designing and building predictive models and optimization engines for use in our trading strategies. Assist in performing regular evaluation of such systems and suggest enhancement ideas
Assist with development efforts to turn experimental models into production-ready systems.
Excellent quantitative problem solving skills, attention to detail, a hunger and curiosity about data, and a drive to continually learn and grow.
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.
Proficiency and experience in model building approaches (descriptive data analysis, feature engineering, model selection, tuning, validation, point/interval prediction) with a solid grasp of underlying theory.
Proficiency and experience in a number of regression models (e.g. Generalized linear, Smoothing, LASSO, etc), machine learning models (e.g. KNN, SVM, ANN, RF, GBM, Deep Learning, etc), and time series models (e.g. ARIMA, GARCH, etc) with a good understanding of underlying theory and parameter tuning approaches.
Proficiency and experience in linear and non-linear optimizations.
Proficiency in R, Python, or MATLAB (at least 6 months, with use in major projects). Must be willing to work primarily in R
Experience with SQL and other database technologies (Cassandra, DynamoDB, etc) is a plus.
Experience with distributed computing and big data systems (Hadoop, Spark, etc) is a plus.
Ability to quickly learn new, complex subject matter and intelligently apply it to solving real-world problems.
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. Statistics, 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.
Participation in modeling competitions (e.g. Kaggle, MCM), personal interest projects, and continual education (e.g. Udacity, Coursera) strongly preferred.
Tios Capital will provide a competitive base salary, with eligibility for bonuses based on individual and company performance. Three weeks of paid vacation, health, and dental insurance are also included.
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