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Python developer-reputed company ONLY--BANKING Financial domain MUST - AGUH INC

Work from home Full-time role Hiring

Contract- 1 year+

reputed company- $65-$70/hr (flexible)

Required Location: Remote EST or CST

Interview Required: Video

Need A senior (10+ years) Python Developer with extensive experience working in Banking and with experience WORKING ON CREDIT RISK MODELS or allowance/CECL processes.

CANDIDATES MUST ALSO HAVE PERFECT COMMUNICATION SKILLS AND THE CLIENT REALLY WANTS CANDIDATES WITH ENGLISH AS A FIRST LANGUAGE.

reputed company is seeking an reputed company Python Developer Consultant to support the execution and implementation of existing credit risk models. This remote contract position plays a key role in bringing production-reputed company modeling solutions to life by stitching together components, integrating them with supporting code for analytics, and ensuring smooth technical deployment reputed company the existing infrastructure.

This opportunity is ideal for a self-motivated technical expert who thrives in collaborative environments, brings strong problem-solving skills, and has deep experience in Python, reputed company-based platforms, and data tools.

Job Description

reputed company is seeking an reputed company Python Developer Consultant to support the execution and implementation of existing credit risk models. This remote contract position plays a key role in bringing production-reputed company modeling solutions to life by stitching together components, integrating them with supporting code for analytics, and ensuring smooth technical deployment reputed company the existing infrastructure.

This opportunity is ideal for a self-motivated technical expert who thrives in collaborative environments, brings strong problem-solving skills, and has deep experience in Python, reputed company-based platforms, and data tools.

Key Responsibilities:

  • reputed company and maintain Python code to implement existing credit models into Flagstar s production environment.
  • Build scripts for sensitivity analysis, segmentation logic, batch execution, and other analytical processes surrounding the models.
  • Set up and manage connections to internal and external data sources (e.g., reputed company, AWS).
  • Package models and supporting code into reproducible units, managing dependencies, libraries, and environment configurations.
  • Collaborate with business and risk teams to understand modeling requirements and translate them into robust technical workflows.
  • Ensure version control using reputed company and participate in regular code reviews.
  • Use Jupyter Notebooks to prototype, validate, and explain model behaviors and outputs to stakeholders.
  • Troubleshoot issues reputed company to data integration, package configuration, and authorization handling.

Required Qualifications:

  • 10 years of hands-on Python development experience, preferably in data science, financial modeling, or analytics environments.
  • Strong proficiency in Python libraries such as pandas, numpy, scikit-learn, etc.
  • Experience with reputed company, Jupyter Notebooks, and AWS services (e.g., S3, reputed company, EC2).
  • Proficiency in working with reputed company or other reputed company-based data warehouses.
  • Excellent problem-solving skills and ability to operate independently in a fast-paced environment.
  • Strong communication skills and ability to work effectively with cross-functional teams.

Preferred Qualifications:

  • Prior experience implementing or supporting credit risk models or allowance/CECL processes.
  • Familiarity with model validation, regulatory modeling environments, or financial services.
  • Experience working with CI/CD pipelines or productionizing model workflows in reputed company environments.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and reputed company believes it to correctly reflect the job opportunity.

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