Telecom AI & Data Analytics Lead

Techner Ltd

New Jersey

Hybrid

GBP 89,000 - 133,000

Full time

14 days+

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Benefits offered by this job

Long-term engagement

Job summary

Techner Ltd in the United States (Remote) is seeking a seasoned telecom analytics expert to dive into wireless and customer data, uncover untapped AI-enabled opportunities, and help shape smarter networks and better customer outcomes.

You will bridge business teams, data scientists, and AI engineers, turning business problems into clear, data-backed AI recommendations, while advising on data quality and feature design for real-world model applications.

Qualifications

  • 10+ years in telecom/wireless data analytics.
  • Experience with RAN, KPIs, and customer experience metrics.
  • Strong SQL skills and large-scale data platforms.
  • Experience collaborating with AI/ML or data science teams.

Responsibilities

  • Dig into large wireless datasets to surface trends, issues, and growth opportunities.
  • Bridge between business teams, data scientists, and AI engineers, translating problems into data-backed AI recommendations.
  • Advise on data quality, feature design, and real-world context for model applications.
  • Identify data-driven automation, prediction, and smarter network and customer operations.
  • Set goals and roadmaps aligned with business priorities.
  • Brief senior leaders with dashboards and reports that simplify complex data.
  • Assess data readiness for predictive ML and GenAI use, prioritizing projects by impact.

Skills

SQL
Telecom analytics
Stakeholder mgmt
GenAI exposure
Executive communication
Independent work

Job description

Techner Ltd in the United States (Remote) is seeking a seasoned telecom analytics expert to dive into wireless and customer data, uncover untapped AI-enabled opportunities, and help shape smarter networks and better customer outcomes.

You will bridge business teams, data scientists, and AI engineers, turning business problems into clear, data-backed AI recommendations, while advising on data quality and feature design for real-world model applications.

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