Lead Machine Learning Engineer, Marketing Mix Modeling

Adobe Adobe · Enterprise · San Francisco, CA +3

Lead Machine Learning Engineer role focused on designing, developing, and deploying advanced causal Marketing Mix Models (MMM) for Adobe's global marketing budget decisions and business growth insights. The role involves building foundationally solid, frequently refreshed production models, collaborating with cross-functional teams, and measuring marketing ROI.

What you'd actually do

  1. Develop both descriptive and predictive MMMs that accurately measure the incremental impact of marketing and non-marketing drivers
  2. Expand our modeling solutions to support a growing number of geographic locations and product groups
  3. Integrate additional measurement methodologies and data to ensure accurate measurement of marketing return on investment
  4. Measure both short- and long-term impact of marketing to guide budget allocation across funnel stages to drive sustainable business growth
  5. Communicate model results effectively to partners and executives

Skills

Required

  • MS/PhD in Economics, Statistics, Physics, Mathematics, Computer Science, or a related quantitative field
  • 3-4 years of experience in developing and operationalizing MMM and marketing science solutions
  • Strong technical expertise in MMM and ML algorithms
  • Experience with experimentation/causal inference methods
  • Experience in deploying models from development to production environments
  • Proficiency in ML programming languages like Python, R, etc.
  • Proficiency in data querying languages (e.g. SQL)
  • Experience with cloud platforms for scalable model training and deployment
  • Strong communication skills
  • Ability to explain technical terms to business stakeholders
  • Ability to build positive working relationships and collaborate in cross-functional teams

Nice to have

  • A curious mind, passion, and motivation to learn new skills, tools, and techniques!

What the JD emphasized

  • operationalizing MMM
  • deploying models from development to production environments
  • scalable model training and deployment

Other signals

  • Develop both descriptive and predictive MMMs that accurately measure the incremental impact of marketing and non-marketing drivers
  • Expand our modeling solutions to support a growing number of geographic locations and product groups
  • Integrate additional measurement methodologies and data to ensure accurate measurement of marketing return on investment
  • Measure both short- and long-term impact of marketing to guide budget allocation across funnel stages to drive sustainable business growth
  • Communicate model results effectively to partners and executives