Data Scientist I

Through our dedicated associates, Conduent delivers mission-critical services and solutions on behalf of Fortune 100 companies and over 500 governments - creating exceptional outcomes for our clients and the millions of people who count on them. You have an opportunity to personally thrive, make a difference and be part of a culture where individuality is noticed and valued every day.

Job Overview

Do you enjoy building and managing the deployment systems that power enterprise-grade data science and AI applications at scale? We're seeking a Cloud Deployment Engineer to join our Platform Engineering Practice and own the deployment pipelines, release processes, and operational stability of our cloud-first analytics platforms on Azure. You'll design deployment methods, implement automation, troubleshoot complex deployment failures, and ensure our solutions reach production reliably, securely, and repeatably.

Why This Role Is Critical: This position is foundational to our ability to deliver secure, scalable, and reliable cloud-native solutions to our clients. The engineer in this role becomes the trusted infrastructure partner to our data science, analytics, and AI teams ,ensuring systems remain available, secure, and cost-effective while supporting rapid innovation cycles.

The candidate in this role will join a growth path that expands cloud infrastructure expertise:

• Design and implement deployment methods, pipelines, and processes for cloud-first solutions on Azure including App Services, Azure Functions, Container Registry, and storage services

• Build and optimize CI/CD pipelines in enterprise cloud environments using Azure DevOps to automate testing, building, and deploying applications

• Implement Infrastructure as Code (IaC) practices using Terraform, ARM templates, or Bicep for repeatable, version-controlled deployments

• Containerize applications using Docker and manage container deployments in Azure environments

• Troubleshoot and resolve complex failures at all stages — from deployment pipelines through to running production systems — including reading and diagnosing issues at the code level