Platform Data Analyst
Role summary by JobGrid
Platform Data Analyst at Runware: Remote, United Kingdom; Full time. This listing is part of JobGrid's Remote data analyst jobs from public company career pages. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.
- Location and workplace: Remote, United Kingdom
- Role classification: Full time
- Source freshness: checked by JobGrid on 2026-05-30.
- Application path: candidates continue to the employer application page with non-personal referral tags.
About Runware
Runware is building a high-performance, full-stack AI media-creation platform — empowering developers and companies to generate any type of media instantly. As we scale fast and integrate increasingly complex models, we need stronger visibility, analytics, and monitoring across the whole platform stack.
We’re looking for a Data Expert (Analytics + Monitoring + Observability) to help us better understand, measure, and optimize how the Runware platform performs at scale — internally and for our clients.
🎯 Mission
Your main goal is to give Runware full visibility over:
- End-to-end inference performance
- Integration usage and model activity
- Errors, delays, bottlenecks, regressions
- Internal and client-facing analytics dashboards
- Health and performance of production pipelines
You will provide the data insights that allow engineering, ML, backend, DevOps, and leadership to make informed decisions — and to continuously improve performance and reliability.
🧩 What You Will Do
Performance Monitoring & Benchmarking
- Build and maintain E2E inference time tracking (global and per-model).
- Monitor how implementation changes impact total request latency.
- Detect regressions introduced by suboptimal code paths.
- Provide automated alerts & historical trends.
Usage & Analytics Reporting
- Build dashboards for internal use (engineering, product, leadership).
- Provide client-facing usage dashboards (requests, errors, success rate, performance).
- Support clients who need visibility to debug their integrations.
- Track model-level usage, API endpoints usage, adoption metrics, etc.
Platform Observability
- Implement metrics, logs, and traces that help the entire platform scale smoothly.
- Work closely with DevOps & backend teams to improve system observability.
- Provide insights that guide infra decisions (GPU allocation, autoscaling, caching, batching, etc.).
Data Infrastructure Ownership
- Select and maintain tooling (e.g., Prometheus/Grafana, Datadog, OpenTelemetry, ELK, BigQuery, etc.).
- Ensure data pipelines are reliable, accessible, and always up-to-date.
- Build simple, easy-to-read dashboards for both technical and non-technical teams.