Senior-Advanced Analytics at AT&T in Atlanta, Georgia

Job Description:

At AT&T our amazing people, combined with a culture that thrives on collaboration and creativity, are the foundation that create a great place to work.  We empower our people to push the limits of what’s possible, driving groundbreaking innovation each and every day. We’re redefining the future of entertainment and mobile communications, and we’re ready for you to play a big part in that future too.

Overall Purpose

Experienced data scientist position that uses highly advanced skills in the use of predictive sciences for voice virtual assistant and risk management - predictive modeling, statistical methods, multivariate analysis, decision trees, clustering/segmentation analysis, time series analysis, survival analysis, forecasting, association rules, data mining, test and control experimentation (design of experiments/DOE), sampling, trend analysis, visualization techniques, and other statistical or data analysis techniques to analyze large data files from both internal and external sources to explain or predict behavior and or solve a variety of business problems.  Will perform networking and research of business unit functions and underlying processes, identify corporate data sources and uses for data, and translate results into meaningful financial impacts and operational recommendations.  Implementation of statistical methods and interactive tools for analysis of client’s business challenges.

Key Roles and Responsibilities

• Participate in client engagements in enhancing current statistical models and develop new models for business needs or design of experiments for test/control analysis and business process trials.
• Consult with cross-functional teams on matters relating to statistics, knowledge discover, data modeling, and analytics.
• Own predictive models/ML and DOE/A-B testing areas of voice virtual assistant customer interactions and negotiations
• Develop business context for environment and ML uses/applications and deep knowledge of data inputs, outputs, and statistical testing/modeling
• Write/Run data extraction algorithms to acquire data from primary or secondary data sources and ability to describe/direct data requests for representative data necessary for analyses
• Develop statistical tests and predictive solutions to make business recommendations for decisioning
• Train/develop models, run evaluation experiments, and perform statistical analysis of results and refine models
• Develop understanding of data framework and how it relates to business use, specific process time points, and make recommendations for any new data needs.  Coordinate with data engineers to ensure data is representative of analysis solutions.
• Use of data analytics and other strategies that optimize statistical efficiency and quality
• Interpret data, analyze results using statistical techniques and provide ongoing reports
• Identify, analyze, and interpret trends or patterns in complex data sets
• Filter and “clean” data by reviewing computer reports, printouts, and performance indicators to locate and correct code problems
• Work with management to prioritize business and information needs
• Perform Ad Hoc Data Analysis and reporting for model performance
• Locate and define new process improvement opportunities for testing and predictive modeling
• Partner with systems team to design, plan, execute, monitor, and evaluate DOE/A-B test experiments
• Responsible for regular reports/analyses while the trials are in progress, as well as analyze the results from the completed trial
• Responsible for developing presentation (i.e. PowerPoint-PPT) to share end-end storyboard for analytical initiative, including appropriate visualization
• Use of NLP statistical techniques to transform natural language data into useful features via identification of patterns with voice to text data, to feed classification algorithms, select appropriate annotated datasets for Supervised Learning methods, and use effective text representations to transform natural language into useful features which can be used as attributes/predictors for other negotiation modeling components, decisioning, and in other processes.

Required Skills

• Typically requires a master’s or foreign equivalent degree in Statistics, Data Science or Industrial Engineering.
• 3 years’ experience using ML (machine learning), statistical predictive modeling, multivariate/regression, clustering, time series/survival analysis, DOE(design of experiments), sampling, statistical analysis/testing, text mining/NLP, and visualization techniques; client engagements to solve business challenges and develop processes using data from various inputs and developing statistical solutions for business needs
• 3 years’ experience utilizing analysis tools such as Base SAS, SAS/Macros, SAS/STAT, SAS Enterprise Miner, SAS Viya, R, Python and familiarity with SQL and data management/cleaning techniques to ensure data is representative of statistical analysis, predictive model, or analysis solution. (Python/R skills required)
• Experience in client engagements, interpreting client’s business challenges, and recommendations for statistical analysis solutions (i.e. analytical consulting and solution design)
• Strong understanding of internal business segment or stakeholders and strong presentation skills including visualizations and storyboard of analysis results via PowerPoint.
• Strong financial acumen and analysis experience to determine business impacts for application of statistical solution
• Experience in presentation design, development, delivery, and communication skills to present analytical results and recommendations for action-oriented data driven decisions and associated operational and financial impacts.

Principal Functional Skills / Competencies associated with this Title:

• Business Assessment
• Data Analysis - Software
• Data Architecture
• Data Mining and Data Science
• Data Movement Tools
• Graphic Visualization
• Informatics/Information Sciences
• Programming Languages
• Statistics and Actuarial Modeling