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Internship Telecom Data Analyst Jobs (NOW HIRING)

ManTech

Data Analyst

Ashburn, VA

Coursework related and/or prior internship related to data science/analytics * Working knowledge of statistical modeling * Knowledge of Python, R, Scala, or JavaScript * Strong written and verbal ...

Windfall

Data Analyst

San Francisco, CA · On-site

$90K - $120K/yr

At Windfall, data isn't just a resource-it's our product. We are on a mission to democratize access ... Bachelor's degree * 2-4 years of professional work experience (including internships) in an Analyst ...

Windfall

Data Analyst

San Francisco, CA · On-site

$90K - $120K/yr

At Windfall, data isn't just a resource-it's our product. We are on a mission to democratize access ... Bachelor's degree * 2-4 years of professional work experience (including internships) in an Analyst ...

ManTech International

Data Analyst

Ashburn, VA · On-site

Coursework related and/or prior internship related to data science/analytics * Working knowledge of statistical modeling * Knowledge of Python, R, Scala, or JavaScript * Strong written and verbal ...

Crox Consulting Inc

Telecom Expense Analyst

New York, NY · On-site

$65 - $68/hr

Analyze report for data integrity. • Establish/Optimize process to Review Cost Benefit Analyses ... Telecom Services & Expense Management • Experience with project-based financial management ...

Govini

Data Analyst

Arlington, VA · On-site

... or internships, performing national security-related analytics; preference for research ... data manipulation, and data visualization skills * Excellent professional demeanor with a ...

AARP

Data Analyst Intern

Washington, DC · On-site

$28/hr

As a Data Analyst Intern, you will have the opportunity to work closely with our dedicated team ... This internship offers a unique blend of responsibilities, allowing you to develop a diverse skill ...

Air

Data Analyst

Arlington, VA

... or internships, performing national security-related analytics; preference for research ... data manipulation, and data visualization skills * Excellent professional demeanor with a ...

Dental Depot

Data Analyst

Oklahoma City, OK · On-site

Experience: 2+ years of experience in data analytics, reporting, or related technical roles (internships, academic projects, or hands-on experience acceptable). Experience working with structured ...

Boeing

Data Analyst

Long Beach, CA · On-site

$68K - $92K/yr

Data Analyst Company: The Boeing Company We are seeking a Data Analyst to support the Boeing Global ... Exposure to Tableau (academic, internship or personal projects) * Familiarity with Smartsheet or ...

Boeing

Data Analyst

Long Beach, CA · On-site

$68K - $92K/yr

Data Analyst Company: The Boeing Company We are seeking a Data Analyst to support the Boeing Global ... Exposure to Tableau (academic, internship or personal projects) * Familiarity with Smartsheet or ...

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How much do internship telecom data analyst jobs pay per hour?

As of Jun 23, 2026, the average hourly pay for internship telecom data analyst in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What does an Internship Telecom Data Analyst do?

An Internship Telecom Data Analyst assists in collecting, analyzing, and interpreting data related to telecommunications networks and services. They support senior analysts by generating reports, identifying trends, and providing actionable insights to improve network performance and customer experience. Interns may also help with data cleaning, database management, and using analytical tools to visualize data. This role provides an excellent opportunity to learn about telecom systems, data analytics techniques, and industry best practices.

What types of projects and tasks can an Internship Telecom Data Analyst expect to work on during their placement?

As an Internship Telecom Data Analyst, you can expect to be involved in analyzing large datasets related to network performance, customer usage patterns, and service quality. Typical tasks may include cleaning and processing data, generating reports, and assisting with predictive modeling to identify trends or areas for optimization. You may also collaborate closely with engineers, project managers, and other analysts to support ongoing initiatives and present your findings in meetings. This hands-on experience provides valuable exposure to real-world telecom data challenges and helps you develop both technical and teamwork skills.

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

AspectInternship Telecom Data AnalystTelecom Data Analyst
Required CredentialsEnrolled in or recent graduate of relevant degree (e.g., Data Science, Telecommunications)Bachelor's or higher in related field, often with some experience
Work EnvironmentInternship setting, learning-focused, entry-level projectsFull-time professional role, responsible for analyzing telecom data
Employer & Industry UsageTelecom companies, internships for students or entry-level candidatesTelecom companies, ongoing data analysis and reporting

The main difference is that an Internship Telecom Data Analyst is a temporary, learning-focused position for students or recent graduates, while a Telecom Data Analyst is a full-time role requiring more experience and responsibility in analyzing telecom data for ongoing business needs.

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

To thrive as an Internship Telecom Data Analyst, you need a solid foundation in statistics, data analysis, and telecommunications concepts, typically supported by coursework in computer science, engineering, or related fields. Familiarity with data analytics tools such as SQL, Python, Excel, and visualization platforms like Tableau is commonly required. Strong problem-solving abilities, attention to detail, and effective communication skills help interns translate complex data into actionable insights. These competencies enable accurate data interpretation and support informed decision-making within telecom organizations.
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Internship Telecom Data Analyst jobs near you
Lead Data Scientist Propensity & Segmentation (Telecom)

Lead Data Scientist Propensity & Segmentation (Telecom)

Emergere Technologies

Irving, TX • On-site

Other

Posted 12 days ago

Job description

Position: Lead Data Scientist – Propensity & Segmentation (Telecom)
Location: Irving, TX (3 days hybrid onsite)
 
ROLE SUMMARY:
We build the propensity models and customer segmentation frameworks that drive how we target, acquire, and retain millions of households. This is a 100% hands-on role for a seasoned Data Scientist who loves digging into data and owning execution from end to end. We are looking for someone who can write highly optimized, large-scale SQL feature queries, apply rigorous traditional machine learning methods (avoiding rookie pitfalls like data leakage or uncalibrated models), and turn raw data into high-value targeting lists for marketing.
 
If you are a practitioner who thrives on optimizing data pipelines, mastering telecom data structures, and applying core data science principles to large-scale datasets, this role is for you.
 
WHAT YOU WILL DO:
  • Hands-on Feature Engineering: Write, debug, and optimize complex SQL queries on cloud data warehouses. You will build clean feature sets from raw, massive source tables spanning customer billing, network performance, competitive footprint, and geographic data.
  • Predictive & Behavioral Modeling: Build, calibrate, and maintain propensity and "take rate" models utilizing gradient boosted trees (e.g., XGBoost, LightGBM) to optimize marketing spend.
  • Customer Archetypes: Develop unsupervised clustering and segmentation frameworks to group customers and addresses, enabling hyper-personalized marketing workflows.
  • Enforce Core DS Rigor: Engineer features utilizing strict time-series windows to rigorously protect against data leakage, lookahead bias, and overfitting.
  • Model Explainability & Performance: Evaluate and explain model mechanics using SHAP and feature importance. Monitor models in production to detect and remediate data and concept drift.
  • Experimental Design: Collaborate with marketing teams to design A/B tests and randomized control trials (RCTs) to measure true incremental lift and isolate campaign performance from organic consumer behavior.
  • Deliver Actionable Outcomes: Cleanly package outputs into business-ready deliverables, including feature dictionaries, performance tier charts, and scored target lists.
 
TELECOM & GEOSPATIAL REQUIREMENTS (MUST HAVE):
  • Telecom Domain Expertise: 3+ years specifically navigating telecom, broadband, wireless, or subscription-based data structures (e.g., understanding ARPU, churn cycles).
  • Geospatial Literacy: Practical experience using spatial SQL functions (e.g., BigQuery GIS, PostGIS, H3/S2 spatial indexing) to join and analyze location-based data like lat/long coordinates, wire centers, or census tracts.
 
REQUIRED SQL & BIG DATA SKILLS:
  • Advanced Cloud SQL & Tuning: Expert-level SQL proficiency on cloud data warehouses (BigQuery, Snowflake, or Redshift). You must know how to diagnose and fix poorly performing queries, optimize complex window functions, and handle heavy aggregations on tens of millions of rows efficiently.
  • Memory Optimization: Practical experience handling datasets that exceed local memory constraints using batching, sampling, or large-scale data frameworks (e.g., PySpark, Dask, or warehouse-native tools like BigQuery ML/Snowpark).
 
REQUIRED MACHINE LEARNING & EXPERIENCE:
  • Experience: 5+ years of professional experience as an applied Data Scientist building and deploying supervised and unsupervised machine learning models.
  • Core DS Fundamentals: Deep understanding of traditional ML theory, including class imbalance mitigation, feature selection, probability calibration, and experimental design.
  • Business-Centric Evaluation: Ability to evaluate models beyond standard AUC/ROC, focusing on lift charts, precision-recall curves, tier separation, and financial ROI.
  • Python Ecosystem: Advanced proficiency in Python, specifically utilizing the traditional data science stack (pandas, NumPy, scikit-learn, XGBoost, LightGBM) within notebook and script-based workflows.
 

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