Python full stack developer

5 - 10 years

18 - 33 Lacs

Posted:1 week ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Job Description:

Location: Bangalore

Exp: 5-12 Yrs

Python Full Stack Developer

Key Responsibilities:

  • Core Python Development: Write high-quality, maintainable, and efficient Python code for data processing, statistical modeling, and machine learning tasks.
  • Expert-Level Debugging: Act as a key resource for troubleshooting. Systematically investigate, diagnose, and resolve complex bugs in the backend code, data pipelines, and API integrations.
  • Task Execution: Take ownership of assigned tasks, follow technical instructions precisely, and ensure reliable, on-time delivery of work.
  • Code Maintenance & Refactoring: Improve the existing codebase for better readability, performance, and stability.
  • Collaboration: Work effectively with the project lead to understand requirements and provide clear updates on progress and potential roadblocks.

Required Skills & Qualifications:

Advanced Python Programming:

Demonstrable, extensive experience in writing production-grade Python.

Strong grasp of software engineering best practices (e.g., clean code, modular design, testing).

Proficiency with standard Python libraries for data handling, such as Pandas and NumPy.

Exceptional Debugging and Troubleshooting Skills:

A proven ability to perform deep root-cause analysis on complex software issues.

Experience debugging across different layers of an application (e.g., application logic, API calls, data integrity).

Front-End Debugging Awareness:

Basic understanding of HTML, CSS, and JavaScript.

Crucially, the ability to use browser developer tools to analyze console errors, and understand the front-end/backend communication flow

Version Control

Proficiency with Git and standard branching/merging workflows.

Statistical Foundation:

Theoretical and/or practical understanding of core statistical concepts, including probability distributions, regression and classification models and clustering

Proven experience applying these concepts to real-world data is a nice to have

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