Required Skills and Experience

• Programming & Data:
  • Proficiency in Python programming, including experience with data tools like Jupyter notebooks and pandas.
  • Basic knowledge of SQL for querying and validating data.
  • Comfortable handling structured and semi-structured data (e.g., CSV, JSON, tables).
  • Ability to work with APIs or write scripts for task automation (e.g., data extraction, preprocessing, reporting).
• AI/ML & Development:
  • Foundational understanding of machine learning concepts, gained through self-study, online courses, or personal projects.
  • Basic understanding of the software development lifecycle (SDLC) and ability to collaborate in a structured development environment.
  • Awareness of common ML workflow steps: data cleaning, feature engineering, model training, evaluation, and deployment basics.
• Version Control, Collaboration & Delivery
  • Working knowledge of Git and experience using platforms such as Github, GitLab for version control and collaboration.
  • Ability to follow team practices such as branching strategies (feature branches), code reviews, and merge requests.
• Soft Skills:
  • Strong problem-solving skills with the ability to troubleshoot data/model/service issues logically.
  • Clear communication skills for explaining results, assumptions, and technical constraints.
  • Ability to work independently, take initiative, and explore solutions.

Desirable Qualifications

• Experience with FastAPI or Flask, or strong understanding of REST API concepts (requests, responses, status codes, authentication basics).
• Familiarity with Docker for running services/models in consistent environments.
• Experience using tools like Postman for API testing and debugging.
• Basic familiarity with CI/CD pipelines (GitLab, Azure DevOps CI/CD or similar) and concepts like automated testing, linting, and deployment workflows.
• Exposure to monitoring/logging workflows (basic understanding is enough).