Lead Engineer – Data Science

Data Science Engineer & Lead Engineer - Data Science

Location:

Dallas, TX (Hybrid)

Telecom Domain needed.

Build and maintain advanced data science models and analytical tools to generate actionable insights in the telecom sector. Leverage domain knowledge of telecom networks and services to implement scalable data-driven solutions supporting business decisions and product enhancements.

Key Responsibilities:

• Develop statistical and machine learning models for telecom-specific problems such as churn analysis, network performance (NQES, SINR), and customer behavior analysis around Video on Demand and FWA services.
• Prepare, preprocess, and analyze large telecom datasets from wireline and wireless networks, sites, and interfaces.
• Collaborate with software engineers to integrate data science outputs into operational telecom systems.
• Conduct exploratory data analysis and create visualizations to communicate telecom insights effectively.
• Ensure reproducibility, version control, and quality of data science experiments.
• Present findings and recommendations to technical and business stakeholders.

Skills and Requirements:

• Proficiency in Python or R with libraries for data manipulation (Pandas, Num Py), visualization (Matplotlib, Seaborn, Plotly).
• Composer, Data Proc over GCP, Vertex.
  
  AI, Big Query, Teradata
• Understanding H2O is a plus
• Strong foundation in statistics, hypothesis testing, and ML techniques applied to telecom data.
• Familiarity with telecom data sources and metrics including churn, SINR, real-time network data, and service usage patterns.
• Experience with SQL and No
  
  SQL databases managing telecom data.
• Knowledge of cloud-based data platforms and telecom analytics is a plus.

Drive telecom data science projects from conception through deployment while leading a multidisciplinary team. Deliver high-quality data-driven solutions focused on telecom network analytics, customer churn, real-time monitoring, and service optimization.

Key Responsibilities:

• Oversee development, validation, and deployment of data science models solving telecom-specific challenges such as churn, QoS, SINR, and Video on Demand analytics.
• Lead data engineering efforts to build scalable data pipelines from telecom wireline/wireless network sources and real-time data streams.
• Manage team priorities, resources, and timelines ensuring alignment with telecom business objectives.
• Facilitate collaboration across data science, engineering, and telecom domain experts.
• Promote best practices in code quality, testing, and model governance within telecom projects.
• Communicate project progress and technical findings to stakeholders.

Skills and Requirements:

• Proven leadership experience in telecom data science or analytics projects.
• Strong skills in statistical modeling, ML, data engineering with telecom data expertise.
• Proficiency in Python, SQL, and experience with big data platforms (Spark, Hadoop).
• Familiarity with telecom domain knowledge:
  Wireline, Wireless, NQES, churn, real-time data.
• Excellent organizational, communication, and leadership skills.
• Airflow, Data Proc over GCP, Vertex.
  
  AI, Big Query, Teradata
• Understanding H2O is a plus