Quantitative Developer

The Quantitative Developer is responsible for partnering with quantitative researchers and portfolio managers to build enhance and maintain a comprehensive multi-asset strategy ecosystem encompassing ETL workflows alpha and risk modeling backtesting portfolio construction attribution and reporting infrastructure. The incumbent will work closely with researchers to assist with developing production-quality Python code and tools that enhance research and portfolio management efficiency; manage and maintain production and development databases; assist with maintaining production and development databases; and work closely with vendors counterparties and data engineers to build robust pipelines for the investment process. This position will work proactively with the Multi-Asset Strategies team the broader Risk & Portfolio Management Group and will report to the Head of Multi-Asset Strategies.

WHAT YOU WILL DO:

Model Infrastructure Development & Implementation
Writes and refactors code to implement new and existing quantitative investment processes.
Assists with building robust and scalable tools for backtesting and signal generation.
Work with python APIs (including RESTful APIs) to implement ETL process.
Assists with maintaining Python development and production environments.
Writes unit tests and refactors legacy python repos to use modern coding standards.

Data Management
Assists with sourcing cleaning and maintaining all data feeds from various vendors.
Maintains and designs production and development databases.
Builds robust pipelines for daily refresh of data used in modeling and portfolio management.
Assists with overseeing data quality checks version control and metadata governance.
Partners with counterparties and data vendors to establish and maintain data transfer protocols.

WHAT YOU WILL BRING:

Required Education
Bachelors degree from an accredited college or university in mathematics/statistics computer science physics electrical engineering or a closely related field.

Required Experience
None (Analyst).
One (1) year of full-time directly related progressively responsible experience in software engineering quantitative development or related experience (Sr Analyst).
Three (3) years of full-time directly related progressively responsible experience in software engineering quantitative development or related experience (Associate).
Experience with SQL queries and design schemas
Experience with the Python data science stack including NumPy and Pandas.
Experience with version control software including git.
Experience may be concurrent.
A Masters degree in a related area may substitute for one (1) year of the required experience.

Required Registration Certification Licensure
None

Preferred Qualifications
Masters degree or Doctorate degree/PhD from an accredited college or university in mathematics/statistics computer science physics electrical engineering financial engineering economics or a related area.
Intermediate skills in the Python programming language.
Experience working with data science-oriented Python libraries (Pandas SciPy Numpy Scikit-Learn).
Theoretical and Applied Machine Learning Expertise.
Knowledge of markets or strong interest in financial markets.

Knowledge of:
Essential concepts in quantitative decision making and investment strategies.
Probability statistics econometrics and foundational mathematics (e.g. linear algebra calculus).
Machine learning computer science and software engineering principles.
CI/CD pipelines and modern DevOps practices.
Cloud infrastructure orchestration tools.
Financial markets including investment concepts portfolio management valuation metrics and fundamental factors.

Skill in:
Essential concepts in quantitative decision making and investment strategies.
Probability statistics econometrics and foundational mathematics (e.g. linear algebra calculus).
Machine learning computer science and software engineering principles.
CI/CD pipelines and modern DevOps practices.
Cloud infrastructure orchestration tools.
Financial markets including investment concepts portfolio management valuation metrics and fundamental factors.

Ability to:
Solve technical problems independently and proactively.
Contribute to alpha generation through innovative and collaborative solutions.
Work effectively in a professional team environment maintaining strong relationships with internal and external stakeholders.
Adapt legacy systems to modern standards and continuously improve infrastructure.
Manage multiple projects and deliver high-quality results under tight deadlines.