Junior Data Scientist

We are:
Wizeline, a global AI-native technology solutions provider, develops cutting-edge, AI-powered digital products and platforms. We partner with clients to leverage data and AI, accelerating market entry and driving business transformation. As a global community of innovators, we foster a culture of growth, collaboration, and impact.

With the right people and the right ideas, there’s no limit to what we can achieve

Are you a fit?
Sounds awesome, right? Now, let’s make sure you’re a good fit for the role:

Key Responsibilities:

• Design and develop MLOps pipelines for model training, deployment, and retraining.
• Containerize models using Docker and deploy via Azure Databricks or AKS.
• Implement CI/CD workflows with MLflow and GitHub Actions.
• Monitor model performance and data drift using Azure-native tools.
• Collaborate with Data Scientists and Engineers to integrate models into business systems.
• Document, standardize, and optimize ML deployment processes.

Must-have Skills:

• Bachelor's in Computer Science, Data Engineering, or a related field.
• 2–4 years of experience in MLOps, ML Engineering, or DevOps for ML.
• Proficient in Spark and MLflow; strong experience in Databricks and Azure ML.
• Solid Python and SQL skills; knowledge of containers (Docker/Kubernetes).
• Familiar with CI/CD concepts and tools like Azure DevOps or GitHub Actions.

Nice-to-have:

• Familiarity with Kubernetes (AKS), Terraform, and model observability practices.
• Experience deploying Power BI dashboards that consume predictions.

What we offer:

• A High-Impact Environment
• Commitment to Professional Development
• Flexible and Collaborative Culture
• Global Opportunities
• Vibrant Community
• Total Rewards

*Specific benefits are determined by the employment type and location.

Find out more about our culture here.