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Hourly Telecom Data Analyst Jobs (NOW HIRING)

Zayo

Data Analytics Engineer

Denver, CO · Remote

$77.10K - $118.60K/yr

In this role, you will combine deep telecom data expertise with technical acumen and problem ... You'll also analyze existing processes and data pipelines to identify improvement opportunities ...

Apex 2000

SS - AI ML DATA ARCHITECT ROLE

Jersey City, NJ · Hybrid

$66.50 - $85.50/hr

Apply deep understanding of telecom KPIs, network layers, subscriber data, and operational workflows. Enable AI use cases including: Network anomaly detection & rootcause analysis Intelligent NOC and ...

ITTConnect

Data Analyst (Neo4j)

Atlanta, GA · Remote

The end client is in the Telecom area (internet, mobile, cable TV provider). Initial assignment 6 ... Neo4j data analysis. Experience with SQL Strong programming skills in Python or Java Excellent ...

ITTConnect

Data Analyst (Neo4j)

Atlanta, GA · On-site +1

The end client is in the Telecom area (internet, mobile, cable TV provider). Initial assignment 6 ... Neo4j data analysis. * Experience with SQL * Strong programming skills in Python or Java

Managed Staffing

Data analyst I

Austin, TX · On-site

$25 - $28/hr

... Type Hourly Pay Rate USD 20.87-30.29 Markup 40.50% Bill Rate USD 29.32235-42.55745/hr Standard ... Austin Texas 78744 COST ALLOCATION CODE SpeedChart Code Code SC00076290 - Telecom/Telecom ...

Amphenol TCS

Data Analyst

Hamden, CT · On-site

Data Analyst Location: Hamden, CT Amphenol High Speed Products Group is the market leader for high ... the Telecom/Datacom market (Mobile Networks, Storage, Servers, Routers, Switches, etc.). Our ...

Purple Drive Technologies

Network Data Analyst

Tampa, FL · On-site

Analyze OSS/NMS alarm data to identify patterns, trends, and recurring fault signatures * Develop ... Experience with telecom network domains (RAN/Core/IEN) * Knowledge of OSS/NMS/EMS systems and alarm ...

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Hourly Telecom Data Analyst information

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$34K

$82.6K

$136K

How much do hourly telecom data analyst jobs pay per year?

As of May 31, 2026, the average yearly pay for hourly telecom data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Hourly Telecom Data Analyst, and why are they important?

To thrive as an Hourly Telecom Data Analyst, you need strong analytical skills, proficiency in data management, and a background in mathematics or statistics, often supported by a relevant degree or coursework. Familiarity with telecom databases, data visualization tools like Tableau or Power BI, and experience in SQL or Python are typically required. Attention to detail, problem-solving abilities, and effective communication are important soft skills for interpreting complex data and collaborating with teams. These skills are crucial for accurately analyzing telecom data, identifying trends, and supporting data-driven business decisions.

What are the typical day-to-day responsibilities of an Hourly Telecom Data Analyst?

As an Hourly Telecom Data Analyst, your daily tasks often include collecting and analyzing large sets of telecom data, monitoring network performance, and generating reports to identify trends or issues. You may also collaborate closely with network engineers and IT teams to troubleshoot connectivity problems and ensure data accuracy. Additionally, you’ll likely be responsible for maintaining data integrity, updating databases, and presenting findings to management or clients. This role requires strong attention to detail and the ability to work efficiently on time-sensitive assignments.

What does an Hourly Telecom Data Analyst do?

An Hourly Telecom Data Analyst is responsible for collecting, analyzing, and interpreting data related to telecommunications networks and services. They may work with call records, network usage patterns, and customer data to identify trends, optimize operations, and support business decisions. Typically, these analysts work on an hourly basis, handling tasks such as generating reports, monitoring network performance, and ensuring data accuracy. Their insights help telecom companies improve efficiency, reduce costs, and enhance customer experience.

What is the difference between Hourly Telecom Data Analyst vs Telecom Data Analyst?

AspectHourly Telecom Data AnalystTelecom Data Analyst
Work ScheduleHourly, often part-time or project-basedFull-time, salaried
CertificationsTypically no specific certifications requiredOften requires certifications like CCNA, Cisco, or data analysis credentials
Work EnvironmentContract or temporary roles, often in telecom offices or remotePermanent roles in telecom companies or consulting firms
Job FocusData analysis on an hourly basis, project-specific tasksOngoing data analysis, strategic reporting

Hourly Telecom Data Analysts usually work on short-term projects with flexible hours, focusing on specific data tasks without requiring advanced certifications. Telecom Data Analysts tend to have full-time roles with more responsibilities, often requiring certifications and a broader scope of analysis within the telecom industry.

More about Hourly Telecom Data Analyst jobs
What cities are hiring for Hourly Telecom Data Analyst jobs? Cities with the most Hourly Telecom Data Analyst job openings:
What are the most commonly searched types of Telecom Data Analyst jobs? The most popular types of Telecom Data Analyst jobs are:
What states have the most Hourly Telecom Data Analyst jobs? States with the most job openings for Hourly Telecom Data Analyst jobs include:
What job categories do people searching Hourly Telecom Data Analyst jobs look for? The top searched job categories for Hourly Telecom Data Analyst jobs are:
Hourly Telecom Data Analyst jobs near you
Infographic showing various Hourly Telecom Data Analyst job openings in the United States as of May 2026, with employment types broken down into 65% Full Time, 27% Part Time, and 8% Contract. Highlights an 33% Physical, 17% Hybrid, and 50% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Senior AI/ML Data architect with Telecom

GState Consulting LLC

Warren, NJ

$69.50 - $93/hr

Other

Posted 4 days ago

Job description

Role Senior AI/ML Data architect with telecom experience

Location Baskin Ridge ,NJ

Rate -DOE

Infosys/Verizon

Rate : DOE

Job Description ,

We are seeking a Senior AI/ML Data Architect with strong expertise in Large Language Models (LLMs), AI agents, largescale data systems, and endtoend data pipeline creation, specifically within the Telecom domain. This role is responsible for architecting AIready data platforms that power intelligent automation, advanced analytics, and agentbased decision systems across OSS/BSS, network operations, and customer engagement.

The ideal candidate will bridge data architecture, AI/ML enablement, and telecom domain intelligence, enabling scalable, governed, and highperformance AI solutions.

Key Responsibilities:

LLM & AI Agent Architecture

Design and implement LLMenabled architectures, including RAG (RetrievalAugmented Generation) solutions using structured and unstructured telecom data.

Architect and govern AI agents and multiagent systems for automation, diagnostics, decision support, and workflow orchestration.

Enable secure integration of LLMs and agents with enterprise data platforms, APIs, and business systems.

Define best practices for prompt engineering, model orchestration, evaluation, and feedback loops.

LargeScale Data Architecture

Lead the design of largescale, cloudnative data platforms capable of processing highvolume, highvelocity telecom data.

Architect lowlatency and batch data ecosystems handling CDRs, network telemetry, logs, KPIs, customer interactions, and documents.

Select and implement appropriate data architecture patterns such as Lakehouse, Streamingfirst, and Data Mesh.

Data Pipelines & Engineering

Design and oversee endtoend data pipelines covering ingestion, transformation, enrichment, feature creation, and serving layers.

Build AIready pipelines optimized for LLM training, inference, agent context retrieval, and model lifecycle management.

Ensure realtime and batch pipeline reliability using observability, data quality checks, and automated monitoring.

Implement CI/CDdriven pipeline deployments and versioning.

Telecom Domain Enablement

Partner with OSS, BSS, Network Engineering, IT, and Business teams to translate telecom use cases into scalable AI data solutions.

Apply deep understanding of telecom KPIs, network layers, subscriber data, and operational workflows.

Enable AI use cases including:

Network anomaly detection & rootcause analysis

Intelligent NOC and assurance automation

Customer experience analytics & churn prediction

Fraud detection and revenue assurance

Governance, Security & Compliance

Define and enforce data governance, lineage, metadata management, and access control for large data and AI systems.

Ensure compliance with data privacy regulations and secure AI usage across platforms.

Establish responsible AI and LLM governance frameworks.

Technical Leadership

Act as a domain expert and solution authority for AI/ML data architecture.

Define architectural standards, reference models, and reusable frameworks.

Mentor engineers, architects, and data teams.

Contribute to enterprise AI and data transformation roadmaps.

Required Skills & Experience

Experience

12+ years in data engineering, data architecture, or analytics platforms

5+ years working in the Telecom domain (Network, OSS/BSS, 4G/5G)

Proven experience delivering LLMbased and AIdriven data platforms

Technical Skills

Strong expertise in LLMs, RAG architectures, and enterprise AI integration

Handson experience designing AI agents and agent orchestration frameworks

Deep knowledge of largescale data systems (batch & streaming)

Expertise in creating robust, scalable data pipelines

Strong understanding of ML pipelines, feature engineering, and AI lifecycle needs

Advanced SQL and data modeling skills

Cloud experience with enterprisescale AI and data workloads

Domain & Soft Skills

Strong telecom data and operations knowledge

Ability to translate complex technical designs into business value

Excellent communication, stakeholder engagement, and leadership skills

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