Senior Quantitative Developer

Position Description: 

Improves portfolio management by using programming tools -- Fame, Perl, Python, Unix/Linux to gather, process, and analyze data. Applies mathematical and statistical skills and programming languages to craft and develop solutions and products. Utilizes programming languages including R, Java, SQL and Linux, as well as full-stack development knowledge to support the hands-on development of analytical solutions. Designs applications and subsystems on major projects and for/in multiple platforms utilizing Python, C, C++, C#, and Java. Investigates large structured as well as novel data sources to generate alpha using MATLAB and R. Develops core analytical capabilities or model libraries, performing advanced statistical, quantitative, or econometric techniques using SAS. 

Primary Responsibilities: 

• Quantifies investment decisions through sophisticated calculations; using models such as Brinson Factor model, to decompose returns into asset allocation, interaction, and security selection. 

• Uses quantitative techniques and methods, statistics, and econometrics, including probability, linear regression, and time series data analysis to monitor marketplace trends and create accurate projections. 

• Develops or applies mathematical or statistical theory and methods to collect, organize, interpret, and summarizes numerical data to provide usable information. 

• Analyzes and interprets statistical data to identify significant differences in relationships among sources of information. 

• Analyzes sequences of data points collected over time using time series data analysis. 

• Collaborates with business and quantitative analysts to maintain and extend complex calculation engines to measure investment portfolio performance, risk, and attribution. 

• Partners with investment teams on various projects including portfolio construction, risk management, and alpha research. 

• Designs optimal solutions for computing equity and fixed income security level analytics. 

• Formulating attribution models and analytics to meet the needs of investment management teams. 

• Develops quantitative techniques to inform securities investing, equities investing, pricing, or valuation of financial instruments. 

• Creates mathematical or statistical models for risk management, asset optimization, pricing, or relative value analysis. 

• Uses quantitative skills/technical skills to provide performance attribution for customers. 

• Provides suggestions to improve portfolio management. 

• Supports issues with production reports, identify causes of report inaccuracies. 

Education and Experience: 

Bachelor’s degree (or foreign education equivalent) in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, Computational Finance, or a closely related field and three (3) years of experience as a Senior Quantitative Developer (or closely related occupation) developing performance, attribution characteristics, and risk measurement applications using Perl, Python, FAME, Linux, Oracle, and SQL in a financial services environment.  

Or, alternatively, Master’s degree (or foreign education equivalent) in Computer Science, Engineering, Information Technology, Information Systems, Mathematics, Physics, Computational Finance, or a closely related field and one (1) year of experience as a Senior Quantitative Developer (or closely related occupation) developing performance, attribution characteristics, and risk measurement applications using Perl, Python, FAME, Linux, Oracle, and SQL in a financial services environment. 

Skills and Knowledge: 

Candidate must also possess: 

• Demonstrated Expertise (“DE”) developing with Performance Attribution analysis calculation models -- Brinson Hood Beehover, Brinson Fachler, and Multi Asset Class and implementing the quantitative analysis into programs by using complex datasets with programming languages and tools -- Perl, Python, and FAME. 

• DE developing end-to-end application systems -- building front end graphical user interface to write the backend business and math logic that generates the core logic using programming languages -- Python, Perl, Fame, SQL, JavaScript, HTML, and Linux. 

• DE developing investment analysis prototypes and modeling that explain the performance of the investment products compared to their benchmarks using Perl, Python, and FAME. 

#PE1M2