Director-Data Science

AT&T•Dallas, TX

22h•Onsite

About The Position

Directs and leads 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. 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.

Requirements

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).
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.
Can utilize advanced coding methods to produce visualizations (e.g. ggplot, D3.js, etc.).
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.
10+ years of related experience.

Nice To Haves

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.

Responsibilities

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.
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.
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.
Develop custom Machine Learning (ML).
Uses concepts like mlflow to log metrics.
Create visualizations and reports for stakeholders while working closely with cross-functional teams to align efforts with business objectives.
Develop and implement generative AI models, focusing on creating new content or augmenting existing data.

Benefits

Medical/Dental/Vision coverage
401(k) plan
Tuition reimbursement program
Paid Time Off and Holidays (based on date of hire, at least 23 days of vacation each year and 9 company-designated holidays)
Paid Parental Leave
Paid Caregiver Leave
Additional sick leave beyond what state and local law require may be available but is unprotected
Adoption Reimbursement
Disability Benefits (short term and long term)
Life and Accidental Death Insurance
Supplemental benefit programs: critical illness/accident hospital indemnity/group legal
Employee Assistance Programs (EAP)
Extensive employee wellness programs
Employee discounts up to 50% off on eligible AT&T mobility plans and accessories, AT&T internet (and fiber where available) and AT&T phone