Full-Time Lead Data Scientist

Develop and deploy scalable machine learning models using Python and PySpark.

Build and implement end-to-end MLOps frameworks within Snowflake, including feature stores, model registry, and pipelines.

Define and enforce best practices for model testing, monitoring, and deployment governance.

Collaborate with data engineers, product teams, and business stakeholders to deliver actionable ML solutions.

Conduct model validation and performance evaluation, ensuring fairness, robustness, and reproducibility.

Drive efficiency and scalability in ML workflows through automation and distributed computing.

Stay up to date with emerging trends in ML, MLOps, and Snowflake ecosystem to continuously improve solutions.

Requirements:

• Strong expertise in machine learning modeling and algorithm development.
• Advanced proficiency in Python and PySpark for large-scale data analysis and ML workflows.
• Hands-on experience with Snowflake for data processing and ML pipeline implementation.
• Exposure to MLOps practices (model deployment, lifecycle management, governance).
• Solid problem-solving and communication skills, with the ability to engage technical and non-technical stakeholders.
• Experience collaborating across teams in data-intensive environments.
• Familiarity with cloud platforms (AWS, Azure, or GCP) is a plus.
• Excellent written and verbal English.
• Minimum of 5+ years of experience in Data Science, with proven expertise in ML modeling and applied MLOps practices.

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