Sr. Data Scientist
Serve as an Architect specializing in cloud native DevOps and ML Ops solutions using AWS developer tools, Terraform and Git in a hybrid work model. Design scalable automation for application delivery and machine learning workflows that enhance reliability, security and speed of software releases, supporting business innovation and positive societal impact through resilient digital platforms.
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.
-Coordinate closely with application developers data scientists and operations teams to translate complex functional and nonfunctional requirements into practical cloud and DevOps designs that balance performance scalability security and cost efficiency.
-Establish and refine branching strategies and workflow conventions in Git repositories to maintain clean version control practices that support frequent changes traceability and collaboration in a hybrid work environment without disrupting delivery timelines.
-Optimize continuous integration and continuous delivery pipelines across multiple products by configuring automated builds tests security checks and approvals so that releases are predictable auditable and aligned with enterprise governance expectations.
-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.
Certifications Required
AWS Certified DevOps Engineer or AWS Certified Solutions Architect and Terraform certification preferred..
*Please note this role is not able to offer visa transfer or sponsorship now or in the future*
We're excited to meet people who share our mission and who can make an impact in a variety of ways. Don't hesitate to apply—even if you only meet the minimum requirements. Think about your transferable experiences and unique skills that make you stand out.
Salary and Other Compensation:
Applications will be accepted until Aug 12, 2026,
The annual salary for this position is between $ 90,000 - $ 135,000 depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
- 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
Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
申请人可能需要通过现场面试或视频会议的方式参加面试。此外，候选人在每次面试时可能需要出示其当前所在州或政府签发的有效身份证件。
Cognizant 是一家提供平等就业机会的雇主。在招聘过程中，您的申请和候选资格不会因种族、肤色、性别、宗教、信仰、性取向、性别认同、国籍、残疾、遗传信息、怀孕、退伍军人身份或任何其他受联邦、州或地方法律保护的特征而受到影响。
