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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Data Scientist - **Company:** AT&T Inc. - **Location:** Dallas, TX, United States - **Experience:** Expert - **Salary:** $160,900.0 - $270,400.0 - **Contract:** Permanent contract - **Skills:** Data Analysis, Big Data, Cloud Computing, Databases, Data Mining, Data Visualization, Python (Programming Language), Machine Learning, NumPy, SQL Databases, Transmission Control Protocol (TCP), Enterprise Data Management, Data Processing, Feature Engineering, Snowflake, Apache Spark, Pandas, Data Lakes, Pyspark, Core Data, Scikit Learn, Machine Learning Operations, Data Pipelines, Software Library, Databricks - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=63bf45c3b668388b ## About the Role Do you have experience in Survival analysis?, * Strong proficiency in Python, including scikit-learn, pandas, and NumPy, as well as PySpark/Spark and Databricks ML. * Deep expertise in SQL, Databricks, and Snowflake, with demonstrated experience building and owning scalable data pipelines. * Strong knowledge of survival modeling techniques, machine learning methods, and applied statistical analysis. * Strong data visualization, storytelling, and communication skills, with the ability to translate complex analyses into clear, actionable business recommendations. * Experience with MLflow or similar model management and MLOps tools for experiment tracking, deployment, and monitoring. * Master's degree from an accredited university in a quantitative field such as Data Science, Mathematics, Statistics, Engineering, or Physics. * 5+ years of relevant experience in data science, machine learning, advanced analytics, or a related field. Job Contribution: An experienced professional, recognized as an expert, creatively resolving complex issues with broad and in-depth knowledge. Leads significant projects with strategic autonomy, influencing executive decisions. Mentors less experienced staff, implements long-term plans impacting the organization, and frequently collaborates with senior leadership. Supervisor: No TCP Career Step Differentiator: Performs very complex data science work, builds complex business models, and makes recommendations that impact multiple organizations, lines of the business, etc. Education/Experience: Master's degree (MS/MA) required from an accredited University in a Quantitative field of study such as Data Science, Math, Statistics, Engineering or Physics. 5+ years of related experience. Certification is required in some areas. ## Description AT&T is seeking a Lead Data Scientist to join the Mass Market valuation team. In this role, you will develop, deploy, and optimize machine learning models that predict the long-term tenure of AT&T Fiber and AT&T Internet Air customers. These survival models are critical to estimating customer lifetime value and informing strategic business decisions for both new and existing customers. You will run simulations, identify key drivers of customer survival, interpret model outputs for business stakeholders, and translate findings into actionable recommendations. The role also involves working with large, complex data sets and executing core data science workflows, including data extraction, cleansing, feature engineering, model tuning, and statistical analysis, to generate insights and support data-driven decision-making., * Lead the development, deployment, and optimization of survival models for broadband, AT&T Fiber, and AT&T Internet Air customers to support customer lifetime value estimation and strategic business decisions. * Translate complex business problems into actionable insights through end-to-end data science workflows, including data extraction, cleansing, feature engineering, exploratory data analysis, model development, tuning, interpretation, deployment, and ongoing model monitoring. * Design, build, and analyze large, complex data sets from structured and unstructured sources, including data lakes, databases, cloud platforms, and enterprise data environments, while ensuring data quality, integrity, and usability. * Use simulation techniques and statistical analysis to identify key drivers of customer survival, interpret model outputs, and deliver clear, actionable recommendations to business stakeholders. * Develop scalable coding solutions using Python and PySpark/Spark, with proficiency in modern machine learning libraries and frameworks to support robust model development and production-ready implementation. * Work across big data platforms such as Databricks and Snowflake to support data processing, model development, experimentation, and deployment in large-scale analytics environments. * Partner closely with cross-functional teams to communicate findings, align analytical solutions with business objectives, and support enterprise innovation through advanced analytics and machine learning. * Provide leadership on complex data science initiatives by mentoring less experienced team members, influencing strategic direction, and driving high-impact projects across multiple organizations and lines of business. ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Vectorize all the things! 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