Senior Manager, Analytics Operations

About the Role

Key Responsibilities

• Ensure that analytics assets (data models, ML, AI, and DI) are reliably and efficiently deployed and maintained in production.
• Set up continuous integration pipelines to automate the testing, validation, and deployment of analytics assets.
• Implement automated monitoring and alerting systems to ensure that any disruptions or anomalies in the analytics assets are promptly addressed.
• Collaborate with data engineers and scientists to understand data and model requirements and ensure seamless integration into production systems.
• Troubleshoot and resolve complex issues related to deployment, performance, and scalability.
• Develop governance policies for data management, model development, and analytics deployment, and scale best practices across the organization.
• Implement robust security measures to protect data assets.
• Participate in decision making and bring strong perspectives to achieve team objectives.
• Stay up-to-date with the latest trends and advancements in MLOps and machine learning technologies.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
• 5+ years of experience in deploying and managing models in production environments.
• Experience leading initiatives related to continuous improvement or implementation of MLOps.
• Ability to work independently and manage a cross-functional team to achieve results.
• Strong understanding of machine learning principles and model lifecycle management.
• Proficiency in programming languages such as Python, PySpark, SQL, Bash/PowerShell.
• Extensive experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Proficiency in cloud platforms (AWS preferred, Azure, Google Cloud) and containerization technologies (Docker, Kubernetes).
• Experience with CI/CD tools (Jenkins, GitLab CI, CircleCI) and version control systems (Git).
• Knowledge of monitoring and logging tools (CloudWatch, Grafana, ELK stack).
• Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.
• Excellent communication skills to articulate complex information clearly across all levels.

Nice to Have

• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Experience with containerization and orchestration tools like Docker and Kubernetes.
• Familiarity with monitoring and logging tools such as CloudWatch, Grafana, ELK stack.
• Experience in the biopharma or healthcare industry is a plus.

Qualifications

• Educational background in Computer Science, Engineering, Data Science, or related fields.
• Minimum 5 years of experience in model deployment and management in production environments.

Benefits & Perks

• Competitive salary
• Annual bonus
• Pension contribution
• Family health insurance
• 27 days of annual leave
• Access to BMS Cruiserath on-site gym
• Life assurance