Senior Quantitative Developer

Fidelity Investments•Boston, MA

1d•$140,000 - $150,000•Hybrid

About The Position

Position Description: Builds high quality, robust, and efficient analytical solutions to improve internal investment processes with quantitative techniques and methods, statistics and econometrics – including probability, linear regression, and time series data analysis. Executes programming deliverables using R, Java, SQL, and Linux. Participates in full stack development projects on the frontend User Interface (UIs) and back-end Application Programming Interfaces (APIs), using Python, R, and SQL. Applies data mining, data modeling, Natural Language Processing (NLP), and Machine Learning (ML) to extract and analyzes information from large structured and unstructured datasets. Develops and implements complex techniques or analytics applications to transform raw data using data-Oriented Programming languages and visualization software.

Requirements

Bachelor’s degree in Mathematical Finance, Quantitative and Computational Finance, Engineering, Statistics, or a closely related field (or foreign education equivalent) and three (3) years of experience as a Senior Quantitative Developer (or closely related occupation) developing software solutions (risk management, portfolio construction, performance analysis, or alpha research) in a financial services environment, using Python, Python data libraries, or Relevel concepts.
Or, alternatively, Master’s degree in Mathematical Finance, Quantitative and Computational Finance, Engineering, Statistics, or a closely related field (or foreign education equivalent) and one (1) year of experience as a Senior Quantitative Developer (or closely related occupation) developing software solutions (risk management, portfolio construction, performance analysis, or alpha research) in a financial services environment, using Python, Python data libraries, or Relevel concepts.
Demonstrated Expertise (“DE”) supporting quant researchers and portfolio engineers by developing quantitative software, using R, Python, Shell Scripting, Git, or SQL; accessing database tables via SQL queries using data from financial data vendors (Bloomberg and MorningStar) in financial calculations; and applying financial methodologies (Linear Regression, Time Series Analysis, or Monte-Carlo Simulation) in the development of applications, subsystems, services, or scripts, to support and enhance portfolio risk analytics.
DE supporting quantitative software development using quantitative concepts and valuation techniques applicable to financial instruments (bonds, stocks, mutual funds, and Exchange Traded Funds (ETFs)); and categorizing financial instruments based on their characteristics to improve portfolio performance and streamline risk management processes, using Python and SQL, to develop risk management algorithms, automate data analysis, and generate comprehensive risk reports.
DE developing quantitative models and performance reports, using Python, Shell, GitHub, SQL, and Tableau; enhancing model optimization process by supporting CPLEX optimizers for institutional clients; and applying financial concepts (alpha distribution, returns attribution, and risk and turnover decomposition) for the core portfolio construction platforms to support and improve post model analytic reports.
DE automating the build and release of quantitative software applications, using version control tools (Git or GitHub), defect tracking tools (Jira and Datadog), Jenkins, Amazon Web Services (AWS), and Autosys, to perform Continuous Integration/Continuous Deployment (CI/CD); and performing application testing, troubleshooting, and debugging to validate data quality for trading platforms, using Docker, PyCharm Debugger, Visual Studio Debugger, and SQL.

Responsibilities

Develops analytical solutions.
Develops and monitors portfolio personalization tools and efforts.
Enables users to run customized portfolio optimizations based on personal inputs.
Ensures all coding test cases are properly defined.
Applies sophisticated analytics and quantitative concepts to support investment needs and develops new solutions.
Adds scale, rigor, and repeatability to research through software development standard methodologies.
Reviews and ensures code format and quality satisfy the general engineering standard, and code documentation is sufficient.
Builds high quality, robust, and efficient analytical solutions to improve investment processes.
Analyzes and interprets statistical data to identify differences in relationships among sources of information.
Evaluates technical data to determine effect on designs or plans.
Identifies relationships and trends in data to determine effects on research results.
Provides technical support to production applications to ensure their stability, performance, and reliability.