Marketing Data Science

Verizon Verizon · Telecom · Irving, TX +1

Marketing Data Scientist at Verizon responsible for developing and analyzing complex sales and marketing campaigns using SQL, Python, and AI tools to drive revenue growth. The role involves extracting data, automating processes, providing quality analysis of results, and ensuring compliance with legal regulations. Requires experience in building, validating, and deploying machine learning models, along with database ETL and various BI tools.

What you'd actually do

  1. Assist in the strategic development of national and regional marketing campaigns, both as standalone initiatives and within broader customer journey frameworks.
  2. Extract data points based off Marketing requirements while working with marketing and sales operations to fulfill a complete life cycle of a marketing and sales campaign.
  3. Assist in a variety of projects within the Marketing Science team focused on automating and simplifying processes, while also providing ad hoc data manipulation and analysis to support marketing and strategy on sales plays.
  4. Provide full quality analysis of results and output prior to delivery to Sales Operations and marketing managers as well as follow up compliance regulation to legal.
  5. Demonstrate high-level strategic thinking by continuously aligning technological and data solutions with overall business strategies.

Skills

Required

  • SQL
  • Python
  • BigQuery
  • AI tools
  • Teradata
  • Alteryx
  • Adobe
  • Marketo
  • Looker
  • Tableau
  • GCP
  • Salesforce
  • Database management and BI tools
  • building, validating, and deploying machine learning models
  • exploring new tools and technologies
  • Database ETL experience

Nice to have

  • Marketing
  • Market Research
  • Technology
  • Computer Science
  • Computer Information Systems
  • Information Systems
  • Data Analytics
  • analytic skills
  • interface with IT, Legal, Marketing Strategy, and external vendors
  • written and verbal communication abilities

What the JD emphasized

  • building, validating, and deploying machine learning models
  • exploring new tools and technologies
  • interface with IT, Legal, Marketing Strategy, and external vendors to take new technologies or data architectures all the way from concept to production

Other signals

  • Develops and deploys machine learning models for marketing campaigns
  • Uses AI tools and analytics methods to drive revenue growth
  • Focuses on automating and simplifying processes with data science