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Data Scientist I @ Conduent

INOnsiteFull-timeJob reference 22446
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About this role

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 • Review infrastructure-as-code and application code for deployment readiness, identifying issues before they reach production • Establish monitoring, logging, and alerting strategies using Azure Monitor, Application Insights, and Log Analytics to maintain deployment health • Compose automation scripts to streamline deployment, configuration, health checks, and operational tasks

Experience Needed:

Required:

• 1+ years industry experience with at least 6+ months hands-on Azure cloud platform work • Demonstrated experience deploying and managing applications on Azure App Services, Azure Functions, or similar PaaS offerings • Demonstrated experience building and maintaining CI/CD pipelines in enterprise environments (Azure DevOps, GitHub Actions, Jenkins) • Strong proficiency in Python for deployment automation and scripting • Hands-on experience with Docker containerization and container deployment in cloud environments • Infrastructure as Code proficiency with at least one tool (Terraform, ARM templates, or Bicep) • Experience with application monitoring platforms (Azure Monitor, Application Insights, Log Analytics) • Strong troubleshooting methodology across the full stack - deployment pipelines, running systems, and application code - with the ability to diagnose and resolve complex multi-component failures

Desirable:

• Networking experience with Virtual Networks, service endpoints, private endpoints, and DNS • MLOps concepts and deployment patterns • Azure Data Factory or similar ETL orchestration tools • Familiarity with compliance frameworks (SOC 2, FedRAMP, HIPAA)

Education:

• BS or Masters degree in Computer Science, Software Engineering, or related technical discipline

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