Senior Data Scientist — Network Performance Analytics

Anya Petrov

Contract · Senior · London

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About the role

We are a UK telecommunications infrastructure company. We operate over 22,000 base station sites and carry a significant share of national mobile data traffic. The data we generate is enormous, structurally complex, and almost entirely temporal. Every base station produces continuous telemetry — throughput, interference, handover events, error rates, carrier utilisation — at intervals that vary by KPI and network generation. We have been collecting this data for a long time. We have not been analysing it as well as we should. We are a large company. We have data teams. They are good teams. But the gap between the scale of data we produce and our analytical capability to extract actionable insight from it is still significant. We are hiring a Senior Data Scientist on a 12-month contract to work specifically on network performance analytics: identifying degradation patterns before they affect customer experience, modelling the relationship between network configuration parameters and quality metrics, and building predictive alerting that our network operations centre can act on rather than just observe.

Responsibilities

Develop anomaly detection models for network performance degradation across our base station estate
Build predictive alerting models that give the network operations team actionable advance warning of quality degradation before it affects customer SLAs
Analyse the relationship between network configuration parameters and quality outcomes — the output should inform both automated and human configuration decisions
Deliver analysis in a form the network operations team can act on — not just a model, but a clear recommendation and an explanation of confidence
Document all models, data sources, and evaluation methodology to enable handoff to the permanent data team at contract end

Requirements

6+ years of data science with specific experience in time-series analytics, anomaly detection, or network/operational data
Python at a senior level — production-quality analysis and modelling code, not just exploratory notebooks
Apache Spark for large-scale distributed processing of telemetry data that does not fit comfortably in a single-node environment
Kafka for real-time event stream processing — experience with telemetry or monitoring data streams is directly relevant
SQL for working with structured network configuration and performance data in our enterprise data warehouse
Statistics at depth: time-series decomposition, anomaly detection methodologies, and the ability to model non-stationary data from network systems that change configuration regularly
Familiarity with telecoms data — LTE/5G KPIs, drive test data, or OSS/BSS systems — is valued but not required for a strong applied data scientist

Benefits

£510 – £660 per day (contract rate, inside or outside IR35 depending on arrangement)
12-month initial contract
Remote-first — our data team works remotely with quarterly team days in London
Access to telemetry at a scale and diversity that is rare outside major telecom operators
Structured knowledge transfer to the permanent team throughout the engagement — not just at the end