Data Scientist/MLOps Lead/Consultant - Contract (8-14 yrs)

Roles Required to Contribute :

Leadership & Strategy :

- Lead the design, development, and implementation of MLOps frameworks and best practices.

- Collaborate with data scientists, data engineers, and IT teams to streamline ML workflows.

- Drive the adoption of MLOps tools and processes across the organization.

Technical Implementation :

- Develop and maintain CI/CD pipelines for machine learning models.

- Ensure seamless integration of Snowflake and Azure services in ML workflows.

- Monitor and optimize the performance of ML models in production.

Collaboration & Communication :

- Work closely with stakeholders to understand business requirements and translate them into technical solutions.

- Provide mentorship and guidance to junior team members.

- Communicate progress, challenges, and solutions to both technical and non-technical audiences.

Mandatory Skillsets :

Technical Expertise :

- Hands-on implementation experience in MLOps and CI/CD pipelines

- Mandate proficiency and working experience in Azure

- Solid understanding of CI/CD pipelines and version control systems (e.g., Git).

- Strong experience with Snowflake and Azure services (e.g., Azure Machine Learning, Azure Data Factory).

- Proficiency in MLOps tools and frameworks (e.g., MLflow, Kubeflow, Airflow).

Programming Skills :

- Proficiency in Python and SQL.

- Experience with containerization and orchestration tools (e.g., Docker, Kubernetes).

Analytical Skills :

- Strong problem-solving abilities and attention to detail.

- Ability to analyze and optimize ML model performance.

Good-to-Have Skillsets :

Additional Technical Skills :

- Experience with other cloud platforms (e.g., AWS, GCP).

Soft Skills :

- Excellent communication and interpersonal skills.

- Ability to work in a fast-paced, collaborative environment.

- Strong project management and organizational skills.