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Python Developer, Quantitative Modeling and Risk

Python Developer, Quantitative Modeling and Risk
Newark, NJ
105,000 - 135,000
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Job Description

PGIM Fixed Income:

PGIM Fixed Income is a global asset manager offering active solutions across all fixed income markets. With 1000 employees and $790bn assets under management, the company has offices in Newark, London, Letterkenny, Amsterdam, Munich, Zurich, Tokyo, Hong Kong, and Singapore. Our business climate is a safe inclusive environment, centered around mutual respect, intellectual honesty, transparency and teamwork. Our leaders are focused on talent & culture; dedicated to fostering growth & development at all levels to develop the industry leaders of tomorrow.

Our Role:

The Technology Solutions Group within PGIM Fixed Income is a dynamic, fast-paced environment, with exciting infrastructure changes underway with senior leadership. We are looking for you to build out scalable applications to support our Portfolio Management, Quantitative, and Risk teams. You will have in-depth technical knowledge in Python and will feel comfortable working within large internal and external data sets and modelling techniques. We want you to see this challenge as a unique and valuable opportunity, so if this sounds interesting, then PGIM could be the place for you.

Your Impact:

  • Build , evaluate and maintain new and existing algorithms and queries at the Data, Logic, and Service layers.
  • Align with the Investment Tech Product Owner and Scrum Master in assessing business needs and transforming them into scalable applications.
  • Build and maintain custom syntax and programming languages for identification of new non specified use cases.
  • Code to manage data received from heterogenous data formats including web-based sources, internal/external databases, flat files, heterogenous data formats (binary, ASCII).
  • Work with industry wide frameworks (Lark, Pandas and NumPy) to leverage new methodologies and optimize application performances
  • Continued development on abstract data models using conditional join mapping
  • Design and support effective storage and retrieval of very large internal and external data set and be forward think about the convergence strategy with our AWS cloud migration
  • Assess the impact of scaling up and scaling out and ensure sustained data management and data delivery performance.
  • Build interfaces for supporting evolving and new applications and accommodating new data sources and types of data.

Your Required Skills:

  • 5+ years of experience in building out core financial trading systems and algorithms in Python.
  • Ability to generate complex queries using conditional join maps
  • Cloud experience (Spark/Scala/EC2/Redshift).
  • Direct experience supporting front office end-users (PM, Quant, Risk) and sound understanding of capital markets within Fixed Income.
  • Knowledge of Jira, Confluence, SAFe development methodology & DevOps.
  • Experience working with high level programming
  • Experience with refactoring and implementation of new functions
  • Experience with one of the caching frameworks.
  • Excellent analytical and problem-solving skills with the ability to think quickly and offer alternatives both independently and within teams. 
  • Proven ability to work quickly in a dynamic environment.
  • Graduate School experience in Finance, Statistics, Economics, Computer Science or a related field.
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