Lead Data Scientist

Lead Data Scientist

AT&T is one of the world’s leading telecommunications and technology companies, serving millions of consumers and businesses across the United States. We are investing heavily in data, analytics, and machine learning to improve customer experiences, optimize decision‑making, and support long‑term business strategy at scale.

Why Join AT&T Data Science:

AT&T data scientists work on complex, high‑impact problems that influence real business outcomes. As part of the data science organization, you’ll partner with cross‑functional teams across marketing, forecasting, pricing, and strategy—using data and machine learning to improve customer experiences and drive growth at mass‑market scale.

As a Lead Data Scientist, you will be responsible for building, deploying, and maintaining predictive machine learning models that support marketing activities across the customer lifecycle.

You will also contribute to data science initiatives that inform business strategy, including offer optimization, forecasting, and pricing.

In this role, you will own end‑to‑end data science solutions, from problem definition and modeling to measurement and stakeholder communication, while serving as a technical leader within project teams.

Key Responsibilities:

• Design, develop, and deploy predictive and machine learning models to support: Customer lifecycle marketing (acquisition, retention and save), Offer and promotion optimization, Pricing and Forecasting and performance tracking.
• Use Python, Spark, and SQL to extract, transform, and analyze large‑scale datasets, ensuring data accuracy, quality, and reproducibility.
• Partner closely with marketing, forecasting, pricing, and strategy teams to translate business requirements into actionable data science solutions.
• Measure and evaluate model performance and business impact, including campaign effectiveness and targeting efficiency.
• Contribute to the continuous improvement of data science methodologies, tools, and analytical processes.
• Communicate analytical findings and recommendations through clear documentation, visualizations, and presentations tailored to diverse audiences.
• Provide technical guidance and informal mentorship to peers through code reviews, modeling discussions, and best‑practice sharing.
• Apply working knowledge of Large Language Models (LLMs) and AI agent concepts to enhance analytics workflows, insight generation, or decision support where appropriate.
• Stay current with advancements in data science, machine learning, marketing science, and applied AI.

Required Qualifications:

• Advanced degree (Master’s or Ph.D.) in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field, with 5+ years of applied data science experience.
• Strong hands‑on experience in data science, particularly in marketing analytics, customer analytics, pricing, or forecasting.
• Proficiency in Python, Spark, and SQL for data analysis and model development.
• Solid understanding of machine learning techniques, including Regression and classification, Clustering and segmentation, Time series and forecasting methods.
• Experience developing and deploying models used in marketing campaigns, offer strategies, pricing analysis, or forecasting.
• Strong communication skills and ability to collaborate effectively with cross‑functional partners.
• This role is critical to maintaining and operating core BB predictive models, including Prospects propensity to buy Fiber/AIA, Fiber customers cross‑sell Wireless propensity/uplift, BB/Fiber Vol churn, upgrade, and mover propensity models, total 20 models. With ongoing BSS migration, these models require extensive and continuous maintenance to address possible data structure changes, product changes during migration.

Preferred Qualifications:

• Experience with experimentation design, A/B testing, or uplift modeling.
• Familiarity with LLMs and AI agent frameworks, including practical use cases and limitations in analytics contexts.
• 5+ years of related experience.

Key Skills/Competency:

• Data Modeling
• Machine Learning
• Predictive Analytics
• Python
• Spark
• SQL
• Marketing Analytics
• Forecasting
• Pricing Optimization
• LLMs / AI Agents