Senior Manager, Analytical Operations - AWS Infra Senior Manager

📍 Job Overview

• Job Title: Senior Manager, Analytical Operations - AWS Infra Senior Manager
• Company: Bristol Myers Squibb
• Location: New Brunswick - NJ, Devens - MA, Seattle 1616 Eastlake - WA
• Job Type: Hybrid (2 days on-site)
• Category: Senior Management, AWS Infrastructure, Data Science, Machine Learning
• Date Posted: 2025-08-01
• Experience Level: 5-10 years

🚀 Role Summary

• Lead the implementation, management, and monitoring of analytics assets life cycle in AWS infrastructure.
• Collaborate with cross-functional teams to streamline the end-to-end model lifecycle.
• Ensure the reliability, scalability, and performance of analytics assets in production.
• Troubleshoot and resolve issues related to AWS infrastructure and analytics assets.
• Stay up-to-date with the latest trends and advancements in MLOps and machine learning technologies.

💻 Primary Responsibilities

• AWS Infrastructure Management: Manage and support AWS infrastructure, including EC2, S3, RDS, VPC, IAM, and other AWS services.
• Troubleshooting: Troubleshoot and resolve issues related to AWS infrastructure, deployment, performance, and scalability.
• Model Deployment & Maintenance: Ensure that analytics assets are reliably and efficiently deployed and maintained in production.
• CI/CD Pipelines: Set up continuous integration pipelines to automate the testing, validation, and deployment of analytics assets.
• Monitoring & Alerting: Implement automated monitoring and alerting systems to ensure prompt resolution of any disruptions or anomalies in the analytics assets.
• Collaboration: Collaborate with data engineers and scientists to understand data and model requirements and ensure seamless integration into production systems.
• Governance & Security: Develop governance policies for data management, model development, and analytics deployment. Implement robust security measures to protect data assets.
• Team Leadership: Lead initiatives related to continuous improvement or implementation of MLOps. Manage and mentor a cross-functional team to deliver complex solutions.
• Stay Current: Stay up-to-date with the latest trends and advancements in MLOps and machine learning technologies.

🎓 Skills & Qualifications

Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.

Experience: 5+ years of experience in deploying and managing models in production environments. Experience with AWS services, infrastructure as code (IaC) tools, and MLOps.

Required Skills:

• Strong knowledge of AWS services (EC2, S3, RDS, VPC, IAM, etc.)
• Experience with infrastructure as code (IaC) tools (Terraform, CloudFormation)
• Strong programming skills in Python, PySpark, SQL, Bash/PowerShell
• Extensive experience with machine learning frameworks and libraries (TensorFlow, PyTorch, scikit-learn)
• Proficiency in cloud platforms (AWS preferred), containerization technologies (Docker, Kubernetes)
• Expertise in CI/CD tools (Jenkins, GitLab CI, CircleCI) and version control systems (Git)
• In-depth 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 and ability to articulate complex information clearly and concisely
• Ability to demonstrate in-depth knowledge and expertise, establishing a strong reputation for themselves and the team
• Sophisticated analytical thought using various data sources and understanding the broader implications of actions and perspectives

Preferred Skills:

• Experience with AWS Lambda, AWS Glue, AWS SageMaker, or other AWS data processing and machine learning services
• Familiarity with Agile methodologies and CI/CD best practices
• Knowledge of pharmaceutical industry-specific data and analytics processes

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

• A comprehensive portfolio showcasing your experience with AWS infrastructure, model deployment, and MLOps.
• Live demonstrations of your projects, highlighting your ability to deploy and maintain analytics assets in production environments.
• Case studies illustrating your problem-solving skills, collaboration with cross-functional teams, and impact on business outcomes.

Technical Documentation:

• Detailed documentation of your AWS infrastructure, including architecture diagrams, deployment scripts, and configuration files.
• Code quality, commenting, and documentation standards for your projects.
• Version control, deployment processes, and server configuration documentation.
• Testing methodologies, performance metrics, and optimization techniques used in your projects.

💵 Compensation & Benefits

Salary Range: $133,710 - $162,000 (NJ), $147,080 - $178,200 (WA), plus incentive cash and stock opportunities (based on eligibility).

Benefits:

• Medical, pharmacy, dental, and vision care
• Wellbeing support (BMS Living Life Better program, employee assistance programs)
• Financial well-being resources and a 401(K)
• Short- and long-term disability, life insurance, supplemental health insurance, business travel protection, and survivor support
• Paid national holidays, optional holidays, Global Shutdown Days, paid vacation, paid volunteer days, sick time off, and summer hours flexibility
• Parental, caregiver, bereavement, and military leave
• Adoption and surrogacy reimbursement, fertility/infertility benefits, support for traveling mothers, child, elder, and pet care resources
• Tuition reimbursement and a recognition program

🎯 Team & Company Context

Company Culture:

• Industry: Pharmaceuticals and biotechnology
• Company Size: Large (27,000+ employees)
• Founded: 1887
• Team Structure: The GPS organization supports drug development from discovery through commercialization and distribution to patients. The Analytics & AI Enablement team focuses on enabling analytics and AI capabilities for GPS stakeholders.
• Development Methodology: Agile methodologies and CI/CD best practices are preferred.

Company Website: https://www.bms.com/

📈 Career & Growth Analysis

• Web Technology Career Level: Senior Manager, Analytics Operations - AWS Infra Senior Manager
• Reporting Structure: Reports directly to the Director, Analytics Operations, GPS Analytics & AI Enablement.
• Technical Impact: Leads the implementation, management, and monitoring of analytics assets life cycle in AWS infrastructure, ensuring reliability, scalability, and performance. Collaborates with cross-functional teams to streamline the end-to-end model lifecycle.
• Growth Opportunities:
  • Lead initiatives related to continuous improvement or implementation of MLOps.
  • Manage and mentor a cross-functional team to deliver complex solutions.
  • Stay up-to-date with the latest trends and advancements in MLOps and machine learning technologies.

🌐 Work Environment

• Office Type: Hybrid (2 days on-site)
• Office Location(s): New Brunswick - NJ, Devens - MA, Seattle 1616 Eastlake - WA
• Workspace Context:
  • Collaborative workspaces with cross-functional teams, including data scientists, software engineers, and IT teams.
  • Access to modern tools, technologies, and resources to support your work.
  • Opportunities for knowledge sharing, technical mentoring, and continuous learning.
• Work Schedule: Standard business hours with flexibility for deployment windows, maintenance, and project deadlines.

📄 Application & Technical Interview Process

Interview Process:

1. Phone Screen: A brief phone call to discuss your qualifications and expectations for the role.
2. On-site Interview: A full-day on-site interview, including technical assessments, behavioral interviews, and meetings with key stakeholders.
3. Final Decision: A final decision will be made based on the feedback from the interview process.

Portfolio Review Tips:

• Tailor your portfolio to highlight your experience with AWS infrastructure, model deployment, and MLOps.
• Include live demonstrations of your projects, showcasing your ability to deploy and maintain analytics assets in production environments.
• Prepare case studies illustrating your problem-solving skills, collaboration with cross-functional teams, and impact on business outcomes.
• Ensure your portfolio is well-organized, easy to navigate, and highlights your unique skills and accomplishments.

Technical Challenge Preparation:

• Brush up on your AWS services knowledge, focusing on EC2, S3, RDS, VPC, IAM, and other relevant services.
• Familiarize yourself with infrastructure as code (IaC) tools, such as Terraform or CloudFormation.
• Review your programming skills in Python, PySpark, SQL, Bash/PowerShell, and your experience with machine learning frameworks and libraries.
• Prepare for questions related to CI/CD tools, version control systems, monitoring and logging tools, and problem-solving skills.

ATS Keywords: AWS, Infrastructure, Model Deployment, MLOps, Data Science, Machine Learning, Cloud Platforms, Containerization, CI/CD, Version Control, Monitoring, Problem-solving, Communication, Analytics, Pharmaceuticals, Biotech

🛠 Technology Stack & Web Infrastructure

AWS Services:

• EC2 (Elastic Compute Cloud)
• S3 (Simple Storage Service)
• RDS (Relational Database Service)
• VPC (Virtual Private Cloud)
• IAM (Identity and Access Management)
• Lambda (Serverless computing)
• Glue (Extract, transform, load service)
• SageMaker (Machine learning platform)

Programming Languages:

• Python
• PySpark
• SQL
• Bash/PowerShell

Machine Learning Frameworks & Libraries:

• TensorFlow
• PyTorch
• scikit-learn

Cloud Platforms & Containerization Technologies:

• AWS (preferred)
• Azure
• Google Cloud
• Docker
• Kubernetes

CI/CD Tools & Version Control Systems:

• Jenkins
• GitLab CI
• CircleCI
• Git

Monitoring & Logging Tools:

• CloudWatch
• Grafana
• ELK stack (Elasticsearch, Logstash, Kibana)

👥 Team Culture & Values

BMS Values:

• Passion: We are driven by a deep desire to discover and deliver innovative medicines to patients.
• Innovation: We foster a culture of curiosity and continuous learning to push the boundaries of what's possible.
• Urgency: We act with a sense of urgency to deliver transformative treatments to patients who need them most.
• Accountability: We take personal responsibility for our actions and their impact on patients, colleagues, and communities.
• Inclusion: We embrace diversity and foster an inclusive culture where everyone feels valued and respected.
• Integrity: We conduct our work with the highest ethical standards and a commitment to patient safety and well-being.

Collaboration Style:

• Cross-functional integration between developers, designers, and stakeholders.
• Code review culture and peer programming practices.
• Knowledge sharing, technical mentoring, and continuous learning.

⚡ Challenges & Growth Opportunities

Technical Challenges:

• Troubleshooting and resolving complex issues related to AWS infrastructure, deployment, performance, and scalability.
• Staying up-to-date with the latest trends and advancements in MLOps and machine learning technologies.
• Collaborating with cross-functional teams to streamline the end-to-end model lifecycle.

Learning & Development Opportunities:

• Lead initiatives related to continuous improvement or implementation of MLOps.
• Manage and mentor a cross-functional team to deliver complex solutions.
• Stay up-to-date with the latest trends and advancements in MLOps and machine learning technologies.

💡 Interview Preparation

Technical Questions:

1. AWS Services: Describe your experience with AWS services, focusing on EC2, S3, RDS, VPC, and IAM. Explain how you have used these services to deploy and manage analytics assets in production environments.
2. Infrastructure as Code (IaC): Discuss your experience with IaC tools such as Terraform or CloudFormation. Explain how you have used these tools to automate the deployment and management of AWS infrastructure.
3. Model Deployment & MLOps: Describe your experience with deploying and managing models in production environments. Explain your approach to MLOps and how you have ensured the reliability, scalability, and performance of analytics assets.
4. CI/CD & Version Control: Discuss your experience with CI/CD tools and version control systems. Explain how you have used these tools to automate the testing, validation, and deployment of analytics assets.

Company & Culture Questions:

1. Company Culture: Describe what you understand about BMS's culture and values. Explain how you would contribute to and align with our culture as a Senior Manager, Analytics Operations - AWS Infra Senior Manager.
2. Team Dynamics: Describe your experience working in a cross-functional team environment. Explain how you have collaborated with data scientists, software engineers, and IT teams to deliver complex solutions.
3. Leadership Style: Describe your leadership style and how you would manage and mentor a cross-functional team to deliver complex solutions. Explain how you would foster a culture of continuous learning and improvement.

Portfolio Presentation Strategy:

• Tailor your portfolio to highlight your experience with AWS infrastructure, model deployment, and MLOps.
• Include live demonstrations of your projects, showcasing your ability to deploy and maintain analytics assets in production environments.
• Prepare case studies illustrating your problem-solving skills, collaboration with cross-functional teams, and impact on business outcomes.
• Ensure your portfolio is well-organized, easy to navigate, and highlights your unique skills and accomplishments.

📌 Application Steps

To apply for this Senior Manager, Analytics Operations - AWS Infra Senior Manager position:

1. Tailor Your Resume: Highlight your experience with AWS infrastructure, model deployment, and MLOps. Include relevant keywords and accomplishments to demonstrate your qualifications for the role.
2. Prepare Your Portfolio: Tailor your portfolio to showcase your experience with AWS infrastructure, model deployment, and MLOps. Include live demonstrations and case studies to highlight your unique skills and accomplishments.
3. Research BMS: Familiarize yourself with BMS's company culture, values, and team dynamics. Prepare for company-specific questions and how you would contribute to our culture as a Senior Manager, Analytics Operations - AWS Infra Senior Manager.
4. Prepare for Technical Challenges: Brush up on your AWS services knowledge, focusing on EC2, S3, RDS, VPC, IAM, and other relevant services. Review your programming skills, experience with machine learning frameworks and libraries, and your familiarity with CI/CD tools, version control systems, and monitoring tools.