Description

You will lead data science initiatives, focusing on predictive modeling, workflow automation, and model deployment within AWS environments.

This role is on-site.

Responsibilities

• Prepare tables, listings, and figures for pharmacometric reports and health authority filings.
• Configure AWS Code and GitHub instances, ensuring connectivity to the AWS Data Lake.
• Build and manage workflows using AWS Step Functions and expose model endpoints as services via SageMaker.
• Mentor junior programmers and develop technologies to improve team workflows.
• Implement algorithms to derive complex datasets and detect data anomalies.

Required Skills

• 10+ years of experience in data science, predictive modeling, and data mining.
• Proven experience in AI/ML Ops, specifically model configuration and deployment in AWS.
• Hands-on experience using SageMaker to expose model endpoints as services.
• Expertise in configuring model invoke points and APIs.
• Advanced SAS programming skills, including SAS DATA step and data manipulation PROCs.
• Proficiency in R and Python.
• Experience with Unix/Linux tools and bash scripting.
• Experience with GitHub and AWS infrastructure.

Preferred Skills

• Experience troubleshooting and debugging complex data pipelines and model deployments.

Key Skills

Education

Any Graduate