Data Science & Machine Learning Requirements

Key Qualifications:

Extensive Python and PySpark Experience: Over 4 years of hands-on coding experience with Python and PySpark, demonstrating strong programming skills and a deep understanding of these languages.

Data Science and Machine Learning Expertise: More than 4 years of experience applying data science, machine learning, and statistical techniques to solve real-world business challenges.

End-to-End Machine Learning Pipeline Development: At least 2 years of experience in building and deploying machine learning pipelines, from initial development through to production.

Machine Learning Lifecycle Management: Over 1 year of experience managing the full lifecycle of machine learning projects, ensuring models are robust and reliable throughout their lifecycle.

Proficiency with Coding Environments: Comfortable and experienced working in JupyterLab and VS Code, with the ability to efficiently code and debug in these environments.

Strong Knowledge of Machine Learning Frameworks: Familiarity with a variety of machine learning frameworks, such as scikit-learn (sklearn), PySpark, TensorFlow, and others.

Collaborative and Independent Working Skills: Ability to effectively work both independently and as part of a team, demonstrating strong collaboration and communication skills.

Additional Skills and Experience (Nice to Have):

Continuous Integration/Continuous Deployment (CI/CD): Experience with CI/CD practices, as well as working with terminal and bash scripting.

Developing Edge Cases: Experience in identifying and building out edge cases to ensure model robustness.

Exposure to Advanced Tools and Frameworks: Some familiarity with Kubernetes, MLflow, and YAML, indicating a willingness to learn and adapt to new technologies.

Curiosity and Problem-Solving Mindset: An inquisitive and curious nature, always looking for new ways to solve problems and improve processes.

This role requires someone who is not only technically proficient but also eager to tackle complex problems with innovative solutions. If you are passionate about data science and machine learning and ready to contribute to a dynamic team, we would love to hear from you!