Data Scientist

TechDigital Group; Atlanta (GA); On-site; USD 90,000 - 150,000; Full time

Job summary

An established industry player is on the lookout for a talented Data Scientist with a strong background in telecom. This role is pivotal in applying advanced analytics and machine learning to drive strategic decisions and enhance customer experiences. You will engage with cross-functional teams to tackle key projects like customer churn prediction and network optimization. Your expertise in data analysis, model development, and telecom-specific data will be essential in creating impactful insights. Join this innovative firm to make a significant difference in the telecom landscape and advance your career in a dynamic environment.

Qualifications

• 7+ years of experience in data science, especially in telecom.
• Strong proficiency in Python or R for data analysis and model development.

Responsibilities

• Analyze telecom datasets to identify trends and patterns.
• Develop and deploy predictive models for customer churn and network optimization.

Skills

Python

R

Machine Learning

Statistical Analysis

Data Manipulation

Problem Solving

Analytical Abilities

Education

Bachelor's degree in Data Science

Master's degree in Data Science

Bachelor's degree in Computer Science

Bachelor's degree in Statistics

Bachelor's degree in Mathematics

Tools

Scikit-Learn

TensorFlow

PyTorch

XGBoost

SQL

Apache Spark

Hadoop

Tableau

Power BI

Matplotlib

Seaborn

Job description

We are seeking a skilled Data Scientist with 7+ years of experience, specializing in the telecom industry. This role involves applying data science, advanced analytics, and machine learning techniques to uncover insights that drive strategic decisions, enhance customer experience, and improve network operations. You will work with cross-functional teams to support key telecom-specific projects, including customer churn prediction, network optimization, and predictive maintenance.

Key Responsibilities

1. Perform exploratory data analysis on large telecom datasets, including customer behavior, network traffic, and service usage, to identify trends and patterns.
2. Develop, validate, and deploy predictive models using machine learning techniques to address telecom challenges, such as customer churn prediction, fraud detection, and network demand forecasting.
3. Clean, preprocess, and engineer telecom data to create robust datasets for model training and improve model accuracy.
4. Design and conduct A/B tests and experiments to assess the effectiveness of new telecom features or campaigns.
5. Use statistical models and algorithms to optimize network performance, improve call quality, and minimize downtime.
6. Create dashboards and reports to communicate insights and KPIs to both technical and non-technical stakeholders.
7. Work closely with product, marketing, and network engineering teams to translate business needs into data science solutions and convey complex insights.

Required Skills & Qualifications

1. Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
2. 3–5 years of hands-on experience as a data scientist, preferably within the telecom industry.
3. Technical Skills:
   1. Strong proficiency in Python and/or R for statistical analysis, data manipulation, and model development.
   2. Proficiency with machine learning libraries and tools such as Scikit-Learn, TensorFlow, PyTorch, and XGBoost.
   3. Advanced SQL skills and experience with telecom data, such as call detail records (CDR) and network logs.
   4. Familiarity with big data tools like Apache Spark, Hadoop, or Hive for large-scale data processing.
   5. Proficiency in visualization tools (e.g., Tableau, Power BI) and libraries (e.g., Matplotlib, Seaborn) to convey findings clearly.
4. Understanding of telecom-specific data, including customer usage metrics, network KPIs, and regulatory requirements.
5. Strong problem-solving and analytical abilities to develop models that address business-specific challenges in telecom.
6. Ability to communicate complex data insights to stakeholders at all levels and collaborate effectively across functions.

Preferred Qualifications

1. Advanced Machine Learning & NLP: Experience with deep learning, natural language processing (NLP), or anomaly detection for telecom applications like sentiment analysis or network monitoring.
2. Telecom Protocols & Standards: Familiarity with telecom standards, including LTE, 5G, and telecom-specific protocols.

Certifications: Relevant certifications like AWS Certified Machine Learning, Google Professional Machine Learning Engineer, or telecom-related certifications.