Quick Summary
Architect, execute, and streamline path-to-production workflows for custom data science applications, interactive dashboards, and API models developed in Python and R.
$100k - $130k. The estimate displayed represents the typical salary range for this position based on experience and other factors.
Requirements
~1 min readTarget salary range: $100k - $130k. The estimate displayed represents the typical salary range for this position based on experience and other factors.
We are seeking a highly skilled Data Scientist with a strong background in software deployment, platform engineering, and path-to-production strategies for data science applications. In this role, you will bridge the gap between data science development and enterprise IT infrastructure, ensuring that custom application models written in Python and R are smoothly, securely, and reliably deployed, monitored, and maintained in production.
Responsibilities
~1 min read- →Path-to-Production Deployments: Architect, execute, and streamline path-to-production workflows for custom data science applications, interactive dashboards, and API models developed in Python and R.
- →CI/CD & Automation: Partner closely with DevSecOps team to design, build, and maintain robust CI/CD pipelines to automate testing, build, and deployment processes for analytics projects.
- →Application & Model Monitoring: Implement and maintain robust application monitoring, logging, and metrics tracking to observe runtime health, system resource utilization, latency, uptime, and model drift in production environments.
- →Environment & Image Maintenance: Manage, build, and update custom container images and runtime environments to ensure reproducibility and consistency across development, staging, and production environments.
- →Cybersecurity & Compliance: Partner closely with Cybersecurity and Governance teams to ensure all application deployments adhere to strict cybersecurity policies, vulnerability patching schedules, and enterprise compliance postures.
- →Troubleshooting & Incident Response: Act as the primary technical point of contact for diagnosing, debugging, and resolving deployment, environment, performance bottlenecks, and runtime errors for live data science applications.
Location & Eligibility
Listing Details
- First seen
- October 6, 2026
- Last seen
- October 6, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 56%
- Scored at
- October 6, 2026
Signal breakdown
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