Director, Causal Analytics & Growth Strategy

AT&T; Dallas (TX); On-site; USD 211,000 - 316,000; Full time

Benefits offered by this job

Medical/Dental/Vision coverage

401(k) plan

Tuition reimbursement program

Paid Parental Leave

Paid Caregiver Leave

Sick leave beyond state/local law

Adoption Reimbursement

Disability Benefits

Life and AD&D insurance

Employee discounts

Job summary

AT&T in Dallas, Texas seeks a Director of Advanced Analytics to lead causal measurement, MMM integration, and AI-enabled analytics across marketing investments. You will design experiments, build scalable models, and translate insights into executive decisions driving growth and efficiency.

The role requires strong leadership, scientific rigor, and the ability to partner with senior stakeholders to embed evidence-based decision making across the organization.

Qualifications

• Deep expertise in causal measurement and advanced methodologies including RCTs, geo experimentation, synthetic controls, and Bayesian approaches.
• Ability to translate causal assumptions into graphical/structural models and research design.
• Proven track record of operationalizing frameworks that combine MMM, experimentation, and AI-enabled analytics into business recommendations.

Responsibilities

• Establish AT&T’s Marketing Causal Truths by integrating causal inference, MMM, experimentation, and AI-enabled analytics.
• Scale Marketing Experimentation with governance and Test & Learn programs across multiple channels.
• Translate insights into decision-ready recommendations influencing strategy and investment decisions.
• Lead and develop a high-performing team of causal measurement experts.

Skills

Causal measurement

Data analysis

Experiment design

Executive storytelling

AI-enabled analytics

Tools

MMM

DAGs

SCMs

Predictive analytics

Job description

AT&T in Dallas, Texas seeks a Director of Advanced Analytics to lead causal measurement, MMM integration, and AI-enabled analytics across marketing investments. You will design experiments, build scalable models, and translate insights into executive decisions driving growth and efficiency.

The role requires strong leadership, scientific rigor, and the ability to partner with senior stakeholders to embed evidence-based decision making across the organization.