Hello,
Hope you are doing great today.
Please go through the below requirement and if you have any suitable profiles send them to me ASAP
Please send resume at krishna@unitedleos.com or reach me at 972-497-2365
Model Implementers - Python Programmers
Location: NY
Description:
• Implement statistical, economic, econometric or other mathematical models/code for Chase's consumer bank models in Python
• Ability to translate existing Excel / SAS Model implementations into requirements and high-performance Python implementation
• Work with Enterprise Data Warehouse (ICDW/Teradata) staff members to map variables from their source systems to tables and data sets used by the modeling team and to create necessary meta data to document sources and field definitions
• Responsible for all aspects of data management for the modeling team, data sourcing into containers (Numpy/Pandas), Documentation(Sphynx), Acceleration, (Numba/Cython) and graphics (Matplotlib/Ggplot/Bokeh)
• Assist modeling team members with questions surrounding sources of data files and definitions of data fields
• Develop and maintain report-writing programs used by modeling team members.
Minimum Education:
• Undergraduate Degree (Programming or Mathematics related)
• Master's Degree is Preferred
Qualifications:
• Application Developer (Ad Hoc/Statistical Programmer) with 7+ experience years in Python
• Experience with Python programming using Data Containers (Numpy/Pandas), Documentation(Sphynx), Acceleration, (Numba/Cython) and graphics (Matplotlib/Ggplot/Bokeh)
• Translate Excel / SAS Model Implementations into Python
• Ability to produce queries/tables on request - Sourced from Oracle / Teradata Databases
• Preference will be provided to those with demonstrated modeling experience in consumer and retail business banking
• Excellent communication skills, as the incumbent will frequently be called upon to make presentations to senior management and to write documents that describe work products in a clear manner.
Thanks & Regards,
Krishna kanth
972-497-2365
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