Platform Data Analyst
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 8h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 126d ago
The date the source published, not the day we noticed it (2026-05-12). Last seen at its source 3h ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
United Kingdom
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay £74k–98.8k/yr
Middle 50% of 12 listings that do state pay — Operations · all levels · United Kingdom · GBP/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
workable employer's own board first seen 29d ago · last seen 3h ago
The listing
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.
Requirements
Must-Have
- Strong experience with data analytics, observability, or monitoring
- Hands-on with metrics/logging/tracing frameworks (Prometheus, Grafana, Datadog, New Relic, etc.)
- Good understanding of backend systems and distributed architectures
- Ability to turn raw metrics into actionable insights
- Experience building dashboards for internal and external stakeholders
- Familiarity with AI model monitoring (latency, throughput, error codes, GPU utilization)
Nice-to-Have
- Experience with AI/ML infrastructure, inference pipelines, GPUs
- Understanding of Python APIs, FastAPI, or Node environments
- Experience working with high-throughput real-time systems
- Startup or scale-up experience
What You Bring
- A problem-solver mindset
- Proactivity — you like digging into the data and flagging problems before anyone else sees them
- Ability to work with ML, backend, DevOps, and product teams
- Comfort with autonomous ownership
You help Runware go from “it works” to “we know exactly how well it works — and how to make it better.”
Benefits
We’re a remote-first collective, meeting in person twice a year to plan, brainstorm, celebrate wins, and enjoy some face-to-face time. We have core hours for cooperative working and calls, but outside of that your calendar is yours. Work the hours that let you perform at your peak while also building a healthy life.
Our release cycles are fast and intense, but they’re followed by real downtime. After big pushes we expect the team to unplug, recharge, and come back ready & stronger than ever for the next leap.
- Generous paid time off – vacation, sick days, public holidays
- Meaningful stock options – share in the upside you create
- Remote-first setup – work from home anywhere we can employ you
- Flexible hours – own your schedule outside core collaboration blocks
- Family leave – paid maternity, paternity, and caregiver time
- Company retreats – twice-yearly gatherings in inspiring locations
Please note: We are unable to offer visa sponsorship in the UK at this time. Candidates must have existing right to work in the UK.