Principal Quant Developer en Fidelity Investments

Position Description: 

Builds high quality, robust, and efficient analytical solutions to define risk for alternative investment processes. Creates robust, efficient, and responsive solutions used to enhance systems’ productivity and decision-making processes. Assists research teams in developing new models and products that will provide an advantage to the organization in the marketplace, using R, Python, SQL, and Linux. 

Primary Responsibilities: 

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

• Adds scale, rigor, and repeatability to research through software development standard methodologies. 

• Leads the implementation of research projects through the entire software development lifecycle using full-stack implementation. 

• Applies advanced analytics and quantitative concepts to support investment needs and develop new solutions. 

• Develops software system testing and validation procedures, programming, and documentation. 

• Researches, designs, and develops computer and network software or specialized utility programs. 

• Analyzes user needs and develops software solutions. 

• Applies principles and techniques of computer science, engineering, and mathematical analysis. 

• Updates software or enhances existing software capabilities. 

• Confers with systems analysts and other software engineers/developers to design systems and to obtain information on project limitations and capabilities, performance requirements, and interfaces. 

• Develops and oversees software system testing and validation procedures, programming, and documentation. 

Education and Experience: 

Bachelor’s degree in Computer Science, Engineering, Information Technology, Information Systems, Quantitative Finance, or a closely related field (or foreign education equivalent) and five (5) years of experience as a Principal Quant Developer (or closely related occupation) designing and developing internal Python packages, scripts, user interfaces, Application Programming Interfaces (APIs), and database components to support custom portfolio construction and validation workflows within a financial services environment, using Python, Oracle, Snowflake, and Linux. 

Or, alternatively, Master’s degree in Computer Science, Engineering, Information Technology, Information Systems, Quantitative Finance, or a closely related field (or foreign education equivalent and three (3) years of experience as a Principal Quant Developer (or closely related occupation) designing and developing internal Python packages, scripts, user interfaces, Application Programming Interfaces (APIs), and database components to support custom portfolio construction and validation workflows within a financial services environment, using Python, Oracle, Snowflake, and Linux. 

Skills and Knowledge: 

Candidate must also possess: 

• Demonstrated Expertise (“DE”) developing quantitative research software to implement statistical and econometric techniques, including linear regression, volatility modeling, and time series decomposition, to support portfolio construction, risk analytics, and index strategy development across equities, fixed income, and multi-asset classes, using Python, Pandas, and NumPy. 

• DE building modular index construction frameworks, implementing rebalancing engines, and weighting models (market cap, equal-weighted, and factor-based) and corporate action, by developing internal libraries, APIs, and schemas handlers using Python and SQL. 

• DE deploying research-driven applications to production environment using Jenkins for Continuous Integration/Continuous Deployment (CI/CD), Git for version control, and Linux for automation scripting; containerizing components and integrating Python and pipelines with internal scheduling systems to run in Amazon Web Services (AWS) environments, using EC2, Lambda, and S3 services. 

• DE developing Extract Transform and Load (ETL) pipelines to process structured and unstructured financial data from third-party vendors, using Python and SQL; supporting data integration by using Snowflake and Oracle databases via Python libraries; reconciling inputs with internal index models (market cap-weighted, equal-weighted, risk-parity, and target volatility) using Python and SQL; and validating outputs for completeness, timeliness, and methodological accuracy, using rule-based checks, statistical comparisons, and automated Python scripts. 

Salary: $191,922.00 - $201,922.00/year. 

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