Software Engineer

Data Analysis & Visualization: Pandas, NumPy, Jupyter Notebook, Plotly, Dash, Power BI Testing: PyTest, Unit Testing, Integration Testing, API Testing, Test Automation. Architecture: Reusable Components, Shared Libraries, Scalable Frameworks, Performance Optimization Recent job description describing projects: (Has hands-on recent python experience) Developed Python-based analytical services using FastAPI, Django, PostgreSQL, Redis, Pandas, and Numpy Built reusable object-oriented service components, shared libraries, and framework utilities that reduced duplicate development effort

1. Current, Hands-On Python Experience It is critical that candidates are actively writing Python code in their current role. Many of the recent candidates demonstrated past experience but are no longer actively developing, which has led to challenges during assessment. Candidates must be comfortable coding independently and from scratch.

2. Independent Problem-Solving (No AI During Assessment) Candidates are required to complete an on-site technical assessment using their own laptop. AI tools are not permitted during this exercise. The manager has observed that many candidates rely heavily on AI, which limits their ability to demonstrate foundational knowledge and problem-solving skills.

3. Strong Foundation in Python Fundamentals Candidates should be able to: * Write and structure code logically * Build basic functions * Test and validate outputs * Debug independently

The assessment itself is not overly complex; however, it is designed to evaluate core competency and logical thinking.

1. Understanding of Modeling Fundamentals Candidates should demonstrate a solid grasp of foundational modeling concepts, including: * Basic statistical principles * Model assumptions and error terms * Ability to explain their approach clearly