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AT&T Senior-Data Scientist in Houston, Texas

Join AT&T and reimagine the communications and technologies that connect the world. We’re committed to those who seek to discover the undiscoverable and dare to disrupt the norm. Bring your bold ideas and fearless risk-taking to redefine connectivity and transform how the world shares stories and experiences that matter. When you step into a career with AT&T, you won’t just imagine the future – you’ll create it.

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

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. 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.

Qualifications

  • 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 5-8 years experience. Supervisory: No

  • 5-8 years of hands-on data science experience in designing, developing, and delivering machine learning models (e.g., Classification and Clustering) with large volume of data

  • Strong analytical skills to identify data patterns, trends, and relationships from multiple datasets, including data validation, exploratory data analysis, and data visualization

  • Strong programming skills (e.g., Python and Hive/SQL) and business acumen to turn raw data into insights and perform feature engineering required.

  • Strong communication skills to effectively communicate data insights & machine learning model results to technical and nontechnical people

  • Demonstrable track record of dealing well with ambiguity, exploratory work, and delivering results in a dynamic environment

  • 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.

  • Strong grasp of basic statistical concepts and a strong understanding of the theoretical underpinnings of any techniques being utilized.

Ready to join our team? Apply today!

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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.

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