Associate Director-ai Science

Verizon Verizon · Telecom · Irving, TX

Associate Director of AI Science at Verizon, leading a data science team to develop data-driven solutions and insights for network-related problems. The role involves applying advanced data science techniques, building predictive and prescriptive models, and developing network models and data products to contribute to a self-optimizing and healing network. Key responsibilities include data mining, ensuring data quality, exploratory data analysis, identifying OKRs and KPIs, and translating complex findings for stakeholders.

What you'd actually do

  1. Lead a data science and analytics team to create data-driven solutions and insights, applying advanced data science techniques to solve network-related problems, collaborating with other teams across AI&D to build and integrate predictive and prescriptive models that drive value for the business, and working with various business units to ensure that the team's strategy is aligned with broader company goals
  2. Responsible for leading data mining, extraction of valuable insights from large datasets, validation of data quality, and exploratory and targeted data analyses using statistical methods to uncover trends and patterns that can inform business decisions
  3. Lead the development of network models and data products, using network performance data to provide insights for Network Field Engineering and Centralized Planning & Engineering and to build solutions that contribute to a "self-optimizing and healing network"
  4. Identify OKRs and KPIs for various projects to ensure that the economic impact of the models can be continuously measured and validated, and create business cases and translate complex data findings into practical business implications for stakeholders

Skills

Required

  • Python
  • PySpark
  • SQL
  • Pandas
  • NumPy
  • Hadoop
  • Hive
  • BigQuery
  • Apache Kafka/Pulsar
  • Apache Flink
  • Apache Nifi
  • Splunk
  • Omni Sci
  • Java
  • LTE/5G NR
  • core IP protocols
  • RF and Signal Processing concepts
  • statistical modeling
  • predictive analytics
  • time series analytics
  • scikit-learn
  • XGBoost
  • Matplotlib
  • TensorFlow
  • PyTorch
  • OpenCV
  • Keras
  • AWS SageMaker
  • GCP Vertex AI
  • Tableau
  • Qlik Sense

What the JD emphasized

  • 8 years of progressive, post-baccalaureate experience
  • 8 years in manipulating data and drawing insights from large data sets using Python, PySpark, and SQL
  • 5 years with data mining utilizing Hadoop, Hive, BigQuery, Apache Kafka/Pulsar, Apache Flink, Apache Nifi, Splunk, Omni Sci, and Java
  • 2 years with mobile network ecosystems including LTE/5G NR and core IP protocols, applying RF and Signal Processing concepts to real-world scenarios
  • 2 years using AI/ML techniques including statistical modeling, predictive analytics, time series analytics, scikit-learn, XGBoost, Matplotlib, TensorFlow, PyTorch, OpenCV, Keras, AWS SageMaker, GCP Vertex AI, Tableau, and Qlik Sense

Other signals

  • lead data science and analytics team
  • apply advanced data science techniques
  • build and integrate predictive and prescriptive models
  • lead the development of network models and data products
  • build solutions that contribute to a "self-optimizing and healing network"