This position requires office presence of a minimum of 5 days per week and is only located in the location(s) posted. No relocation is offered.
At AT&T, we empower leaders to drive change in a fast-evolving, connected world. Your strategic vision will help serve customers and transform lives through innovative solutions and impactful connections.
Overall Purpose: Directs and lead a large team of professionals who translate business problems into actionable insights through a comprehensive workflow involving coding, data extraction, cleansing, feature engineering, exploratory data analysis, model creation and tuning, visualization, and deployment, leveraging statistical analysis, machine learning, and big data technologies to drive informed decision-making and innovation.
Key Roles and Responsibilities: Typical tasks may include, but are not limited to, the following:
• Data Extraction and Preparation: Collect data from various structured and unstructured sources (datalakes, databases, data warehouses, on cloud, internal, external) and ensure its quality for analysis through cleaning and preprocessing. Designs, builds, and analyzes large (e.g. 100’s of Terabytes or higher as technology advances) and complex data sets while thinking strategically about data use and data design. Tools can include
• Coding Solutions, Algorithms and Feature Engineering: Create relevant features and conduct exploratory data analysis. Codes solutions 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. Coding proficiency required in at least one data science language (Python, R, Scala, etc.), as well as expertise with modern ML packages and libraries (Spark, SciKitLearn, Pandas, PyTorch, TidyVerse, Tensorflow, Keras, Shiny, and/or AutoML tools).
• Model Development, Deployment and Optimization: Build, evaluate, and optimize machine learning models through hyperparameter tuning. Implement models into production, continuously monitor their performance, and ensure they remain explainable and reliable to minimize model decay. Ability to develop custom Machine Learning (ML). Highly proficient in the full AI workflow such as (1) data extraction, cleansing, feature engineering, exploratory data analysis, model selection/creation, hyper-parameter tuning, model interpretation, model retraining and (2) Uses concepts like mlflow to log metrics. Well-versed in Interactive Development Environments (IDEs) such as Databricks Workspaces or Visual Studio Code. 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, and AI- Knowledge Graphs.
• Visualization and Collaboration: Create visualizations and reports for stakeholders while working closely with cross-functional teams to align efforts with business objectives. Can utilize advanced coding methods to produce visualizations (e.g. ggplot, D3.js, etc.).
• Generative AI: Develop and implement generative AI models, focusing on creating new content or augmenting existing data. Generative Models-Understanding of GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and Transformers. Fine-Tuning-Techniques for adapting pre-trained models to specific tasks using smaller, task-specific datasets. Agentics-Understanding of agentic architecture, concepts and optimization of solutions. Prompt Engineering-Crafting effective prompts to guide generative models in producing desired outputs. Retrieval-Augmented Generation (RAG)-Combining generative models with retrieval systems to enhance performance and relevance. Text Generation-Proficiency in using models like GPT-3/4 for generating human-like text. Image Generation-Familiarity with tools like DALL-E and Stable Diffusion for creating images from text descriptions.
Job Contribution: Designs and executes strategies that support the overarching philosophy of the organization. Oversees departmental programs and is often hands-on with the design and implementation of applicable strategies. Typically leads large teams, supervising supervisors as well as career-level staff within the organization. Responsible for influencing decisions regarding the hiring, firing, disciplinary action, promotional activity, and pay decisions for subordinates. Supervisor: Yes
Education/Experience: Master's degree (MS/MA) desired from an accredited University in a Quantitative field of study such as Data Science, Math, Statistics, Engineering or Physics. 10+ years of related experience.
Our Director-Data Science earns between $ 241,500 - $362,300 USD Annual Not to mention all the other amazing rewards that working at AT&T offers. Individual starting salary within this range may depend on geography, experience, expertise, and education/training.
Joining our team comes with amazing perks and benefits:
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If you’re ready to make an impact on our business and your career, bring your bold ideas to a world of possibility. Apply today!
Ready to join our team? Apply today!
Weekly Hours:
40
Time Type:
Regular
Location:
Dallas, Texas
Salary Range:
$241,500.00 - $362,300.00
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 is a fair chance employer and does not initiate a background check until an offer is made.

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