Principal Quantitative Developer

Fidelity Investments•Jersey City, NJ

14h•$173,000 - $183,000•Hybrid

About The Position

Position Description: Develops high-performance enterprise analytics platforms to support proprietary investment risk models across fixed income securities (bonds, mortgage-backed securities, structured products, and derivatives), using C/C++, Python, SQL, and Linux. Performs integration and utilization of financial libraries (QuantLib and MATLAB), along with financial data sources – Intex, Bloomberg, Refinitiv, TIPS, and other market data providers. Performs infrastructure enhancements using modern DevOps practices (Continuous Integration/Continuous Delivery (CI/CD) pipelines, Kafka, Docker, Helm charts, Amazon Web Services (AWS), and Elastic Kubernetes Service (EKS)).

Requirements

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 Quantitative Developer (or closely related occupation) developing, testing, and maintaining software applications, using C, C++, C#, Python, or SQL in a Linux and Windows based distributed environment.
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 Quantitative Developer (or closely related occupation) developing, testing, and maintaining software applications, using C, C++, C#, Python, or SQL in a Linux and Windows based distributed environment.
Demonstrated Expertise (“DE”) performing software development using C, C++ 14/17, STL, Boost, and C# in Linux and Windows environments;
DE performing distributed messaging and data streaming, using Apache Kafka;
DE applying Object-Oriented Programming principles and design patterns;
DE implementing networking protocols, data structures, algorithms, and concurrency models; and processing financial market data using software engineering techniques.
DE performing all stages of Software Development Life Cycle (SDLC) – gathering and analyzing requirements (using SQL and Python) and coordinating the deployment, testing, and continuous enhancement of software applications, adhering to Agile methodologies.
DE performing software application testing, troubleshooting, and debugging (to meet functional and non-functional requirements), using GNU Debugger (GDB), Visual Studio Debugger, Python, and SQL; providing high level technical support to production applications to ensure their stability, performance, and reliability.
DE deploying applications into production environment by establishing a robust CI/CD pipeline with Jenkins, using Git or GitHub for version control and Python or Linux scripting for automation; and containerizing the application components with Docker managed, using Kubernetes helm chart (EKS) within the AWS Cloud EC2 and S3 services.

Responsibilities

Develops software system testing and validation procedures, programming, and documentation.
Researches, designs, and develops computer and network software or specialized utility programs.
Analyzes information to determine, recommend, and plan computer software specifications on major projects, and proposes modifications and improvements based on user need.
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.
Performs independent and complex technical and functional analysis for multiple simultaneous projects.
Performs post-installation testing to identify and resolve technical problems.
Assists in the planning and execution of user acceptance testing.
Develops technical modules in support of complex assignments and multi-phase projects.
Develops comprehensive documentation for multiple applications in support of corporate initiatives.
Partners with investment teams on portfolio construction, risk management, and alpha research projects.
Adds scale, rigor, and repeatability to research through software development standard methodologies.
Implements 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.