Python Developer

Overall Responsibilities: * Python library developer. * Creating R libraries to be used as interface between model R code and generic data ...

Overall Responsibilities:

• Python library developer.
• Creating R libraries to be used as interface between model R code and generic data retrieval API.
• Python and Pyspark package development.
• Communicate and direct model development teams on implementation of statistical models.
• Write specifications and documentation for R interfaces.
• Interface with Quant users and gather feedback on delivered analytical data.
• Communicate needed changes to development team.
• Work with QA team on test plan reviews and assist in QA testing process with requirements clarifications and questions.

Functional Responsibilities: Specific tasks include but are not limited to:

• Work on one of following initiatives within Global Markets Data Analytics group and other projects.
• Liaise with Dev team on defining data structures used in computing modeling.
• Liaise with QA team on explaining requirements and assisting with QA testing process.
• Support UAT process.

Required Skills: Technical / Analytical Skills:

• Experience with advanced R coding including package development.
• R code optimization and memory management.
• Understanding of core R data structures required.
• Understanding of Python and PySpark development.
• Good understanding of test that, dplyr and sparklyr packages.
• Software development background preferred and experience working in Agile environment.
• Comfortable working with UNIX/LINUX environment.
• Understanding of GIT and/or SVN processes.
• Previous experience with RESTful API framework.
• Good understanding of XML and JSON.
• Good comfort level with relational databases and SQL.
• Experience creating interface specification documents, attribute mapping documents, functional specifications.
• Proficiency with MS Excel, MS Word, MS Visio and MS PowerPoint.

Nice to have:

• Experience with Docker, Jenkins, Azure and Openshift.
• Experience with open-source big data technologies (Hadoop, Hive, Impala, MLLIB, Oozie etc.) for large scale data analysis.
• Experience with visualization tools like Tableau.
• Experience with RShiny.
• Knowledge of regression techniques for modeling the relationship between an output variable and several input variables.
• Understanding of regulatory guidelines (CCAR, Basel) around Model Risk Management.
• Working knowledge of various Fixed Income and Equities products, for example Derivatives, FX and Cash Equities.

Essential Skills

• Strong verbal and written communication skills
• Strong analytical and problem solving skills

WORK EXPERIENCE/BACKGROUND: Experience/Background

• 7-8 years working experience