Senior Data Scientist ( Remote)

Responsibilities

• Design robust end to end cloud architectures that integrate AWS CodePipeline, CodeDeploy, CodeCommit, CodeBuild, and CloudFormation to deliver secure and highly automated application release workflows that improve deployment speed and quality across business critical systems.
• Define and implement standard patterns for infrastructure as code using Terraform and AWS CloudFormation enabling consistent, reproducible, and compliant environments that reduce manual effort and operational risk for development and operations teams.
• Develop efficient ML Ops architectures that streamline model training, validation, deployment, and monitoring so that machine learning solutions move reliably from experimentation to production and deliver measurable value to customers and communities.
• Collaborate with application developers, data scientists, and operations teams to translate complex functional and non-functional requirements into practical cloud and DevOps designs that balance performance, scalability, security, and cost efficiency.
• Create detailed architectural diagrams, standards, and documentation for cloud deployments, pipelines, and ML Ops processes ensuring that technical decisions are transparent, reusable, and easy to onboard for new team members and stakeholders.
• Evaluate existing delivery pipelines, infrastructure configurations, and ML workflows to identify bottlenecks and risks then propose pragmatic improvements that increase reliability, resilience, and resource efficiency across environments.
• Collaborate with platform security and compliance stakeholders to embed security by design in CodePipeline, CodeDeploy, and Terraform-based solutions ensuring that encryption, access controls, and audit mechanisms protect sensitive data and services.
• Guide teams in effective use of AWS managed services and DevOps tooling by conducting design reviews, sharing best practices, and providing hands-on support that helps project squads adopt automation and cloud capabilities with confidence.
• Monitor pipeline performance, build times, deployment success rates, and ML model operational metrics then use data-driven insights to tune architectures and processes for continuous improvement and sustainable long-term operations.
• Contribute to enterprise-wide reference architectures and reusable templates for AWS DevOps and ML Ops so that the organization scales innovation consistently and brings reliable digital solutions to market faster with reduced duplication of effort.
• Align architectural decisions with the company purpose and sustainability goals by favoring efficient resource usage, resilient systems, and ethical ML practices so that technology solutions positively impact clients, employees, and broader society.

Qualifications

• AWS Certified DevOps Engineer or AWS Certified Solutions Architect certification required.
• Terraform certification preferred.

Benefits

• Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long-term/Short-term Disability
• Paid Parental Leave
• Employee Stock Purchase Plan

Pay

The annual salary for this position is between $90,000 - $135,000 depending on experience and other qualifications of the successful candidate.

Schedule

Not specified

Company

Cognizant