Overall Purpose:
This career step requires expert 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 will be used internally by business units to accurately integrate disparate data sets, predict buying behavior of customers, and solve other related business problems.
- Designs, builds, and analyzes large 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: Expert level technical professional. Advisor on technical knowledge and 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. PhD preferred in a Quantitative field of study such as Data Science, Math, Statistics, Engineering or Physics.
Experience: Typically requires 8-10 years experience.
Supervisory: No
Our Principal-Data Scientist, earn between $139,900.00 to $233,200.00, Not to mention all of the other amazing rewards that working at AT&T offers. From health insurance to tuition reimbursement and paid time off to discounts on products and services just to name a few. There is a lot to be excited about around here. Individual starting salary within this range may depend on geography, experience, expertise, and education/training.
AT&T will consider for employment qualified applicants in a manner consistent with the requirements of federal, state and local laws