**Job Description:** Overall Purpose: THIS JOB REQUIRES APPROVAL FROM THE COMP JOB FAMILY OWNER. This career step requires intermediate level experience. The Data Scientist translates business problems to insights and codes solutions using the following typical workflow; data extraction, cleansing, feature engineering, exploratory data analysis, model selection/creation, hyper-parameter tuning, model interpretation, model retraining, business process and/or system implementations, high level proof of concept and trials, visualization, deployment to production, post deployment ML ops monitoring/diagnosis/resolutions. Key Roles and Responsibilities: Proficient in statistical design of experiments (factorial, response surface modeling, Plackett-Burman, central composite designs, Box-Behnken, etc.) in order to validate proof of concepts in a production environment, protect against selection and/or emergent bias and to allow simultaneous trials without cross-trial interference. While this emphasis for this role is on the application of modern techniques, it is assumed that candidates have a strong grasp of basic statistical concepts and a strong understanding of the theoretical underpinnings of any techniques being utilized. The data models created may be used internally and by business units to solve business problems, create income generating models, or to identify improved business processes for cost savings opportunities. Designs, builds, and analyzes large (e.g. 100s of Terabytes or higher as technology advances) and complex data sets from various structured and unstructured sources while thinking strategically about data use and data design. Proficiency in algorithm categories such as Supervised Learning, Unsupervised Learning, Optimization Algorithms, Deep Learning, AI-Computer Vision, Natural Language Processing, Deep Reinforcement Learning, Search Algorithms, AI- Knowledge Graphs. Coding proficiency required in at least one data science language (Python, R, Scala, and SQL), as well as expertise with modern ML packages and libraries (SciKitLearn, Pandas, PyTorch, TidyVerse, Tensorflow, Keras, Shiny, and/or AutoML tools). Proficiency in cloud AI technologies desired, as this position implements AI solutions within the target AI architecture led by the Data Council/Data Review Board. Ability to organize and crisply communicate insights from analysis of large data sets in an intuitive manner to non-technical business partners. Job Contribution: Intermediate level technical professional. Subject matter technical knowledge within a discipline and sound understanding of ATT technologies. Education: Required Masters degree from an accredited University in a Quantitative field of study such as Data Science, Math, Statistics, Engineering or Physics. Experience: Typically requires 3-5 years experience. Supervisory: No. **Weekly Hours:** 40 **Time Type:** Regular **Location:** Dallas, Texas **Salary Range:** $148,200.00 - $222,400.00 It is the policy of AT&T to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, AT&T will provide reasonable accommodations for qualified individuals with disabilities. AT&T will consider for employment qualified applicants in a manner consistent with the requirements of federal, state and local laws We expect employees to be honest, trustworthy, and operate with integrity. Discrimination and all unlawful harassment (including sexual harassment) in employment is not tolerated. We encourage success based on our individual merits and abilities without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, disability, marital status, citizenship status, military status, protected veteran status or employment status