MBSE Matlab/mScripting Requirement - ZR_1961_JOB

Satven

4 - 5 years

4 - 7 Lacs

chennai

Posted:1 week ago| Platform:

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Skills Required

software design coding xml data structures json unit testing matlab release management python technical documentation

Work Mode

Work from Office

Job Type

Full Time

Job Description

Thoroughly analyze existing MATLAB codebase, algorithms, data structures, and functionalities to gain a comprehensive understanding of their purpose, implementation details, and underlying mathematical/scientific principles.
Document the intricacies of the MATLAB tools, identifying core logic, dependencies, and potential challenges for migration.
Collaborate with end-users and domain experts of the current MATLAB tools to capture implicit requirements, usage patterns, and critical performance characteristics.
Develop detailed migration plans, including phased approaches, risk assessments, and resource estimates for converting MATLAB components to Python.
Design the architecture and data flow for the new Python-based tools, ensuring scalability, maintainability, and alignment with overall software engineering standards.
Select appropriate Python libraries, frameworks, and methodologies for optimal translation of MATLAB functionalities (e.g., NumPy for matrix operations, SciPy for scientific functions, Pandas for data handling).
Translate complex MATLAB algorithms and numerical methods into efficient, well-structured, and idiomatic Python code.
Implement new features or enhancements as identified during the migration process, leveraging Pythons ecosystem.
Develop robust data processing pipelines and interfaces to integrate with existing or new data sources.
Design and implement comprehensive test suites (unit, integration, regression tests) to ensure functional correctness and numerical fidelity of the Python tools against their MATLAB counterparts.
Perform rigorous validation of results, comparing outputs from MATLAB and Python implementations to ensure accuracy and consistency.
Identify and resolve performance bottlenecks in the Python code, optimizing algorithms and data structures for efficiency.
Utilize profiling tools to benchmark and improve the execution speed of critical components.
Create clear, concise, and comprehensive technical documentation for the new Python tools, including design specifications, API documentation, user guides, and migration reports.
Provide training and mentorship to other team members on the new Python codebase and best practices for scientific computing in Python.
Contribute to establishing coding standards and best practices for scientific Python development within the team.
Work closely with cross-functional teams (e.g., software engineers, data scientists, domain experts) to ensure seamless integration of the migrated tools into existing systems and workflows.
Participate in code reviews, architectural discussions, and agile development ceremonies.
Manage version control (Git) for the Python codebase, ensuring proper branching, merging, and release management.

Skill set:

MATLAB scripting, Python

Domain Knowledge:

Expert-level knowledge of Python syntax, object-oriented programming, and common design patterns.
Deep understanding and hands-on experience with core scientific Python libraries:
NumPy, SciPy, Pandas,
Matplotlib, Seaborn, Plotly/Bokeh: For data visualization and graphical output replication.
Familiarity with other relevant libraries
Ability to read, understand, and debug complex MATLAB code, including knowledge of MATLABs specific data types, functions, and programming paradigms.
Experience with MATLABs toolboxes relevant to the existing tools
Understanding of MATLABs plotting capabilities and GUI development
Solid understanding of common numerical algorithms, linear algebra, differential equations, optimization techniques, and statistical methods.
Ability to identify and address potential numerical precision issues during migration.
Proficiency with Git for version control.
Experience with unit testing (e.g., pytest) and integration testing frameworks.
Knowledge of code quality tools (linters like Flake8, Black) and static analysis.
Understanding of software design principles (SOLID, DRY).
Experience with various data formats (e.g., HDF5, CSV, Parquet, JSON, XML).

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