Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

This role will co-own critical AI deliverables for AT&T Finance Operations, supporting Treasury/Payments, Billing Operations and Corporate Financial Planning. You will 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.

Responsibilities

Collect data from various structured and unstructured sources and ensure its quality for analysis through cleaning and preprocessing.
Design, build, and analyze large and complex data sets while thinking strategically about data use and data design.
Create relevant features and conduct exploratory data analysis.
Code solutions following a 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).
Log metrics using concepts like mlflow.
Create visualizations and reports for stakeholders.
Work 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.

Requirements

Significant experience with AT&T Finance Operations partners, their KPIs, processes and business challenges is preferred.
Coding proficiency required in at least one data science language (Python, R, Scala, etc.).
Expertise with modern ML packages and libraries (Spark, SciKitLearn, Pandas, PyTorch, TidyVerse, Tensorflow, Keras, Shiny, and/or AutoML tools).
Proficiency 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.
Ability to utilize advanced coding methods to produce visualizations (e.g. ggplot, D3.js, etc.).
Understanding of GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and Transformers.
Understanding of agentic architecture, concepts and optimization of solutions.
Crafting effective prompts to guide generative models in producing desired outputs.
Combining generative models with retrieval systems to enhance performance and relevance.
Proficiency in using models like GPT-3/4 for generating human-like text.
Familiarity with tools like DALL-E and Stable Diffusion for creating images from text descriptions.
Performs complex data science work, builds business models, and makes recommendations for improvements.

Skills

Python
R
Scala
Spark
SciKitLearn
Pandas
PyTorch
TidyVerse
Tensorflow
Keras
Shiny
AutoML
mlflow
Databricks Workspaces
Visual Studio Code
Supervised Learning
Unsupervised Learning
Optimization Algorithms
Deep Learning
AI-Computer Vision
Natural Language Processing
Deep Reinforcement Learning
Search Algorithms
AI- Knowledge Graphs
ggplot
D3.js
GANs
VAEs
Transformers
Agentic architecture
Prompt Engineering
Retrieval-Augmented Generation (RAG)
GPT-3/4
DALL-E
Stable Diffusion

Location

Atlanta, Georgia
Dallas, Texas

Work Type

Onsite
Full-time

Experience Level

3+ years of related experience
Senior

Education Level

Master's degree (MS/MA) in a Quantitative field of study such as Data Science, Math, Statistics, Engineering or Physics

Salary/Compensations

$139,000.00 - $233,500.00 USD Annual

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

About the Company

AT&T and its subsidiaries are committed to equal employment opportunity.
AT&T is a fair chance employer and does not initiate a background check until an offer is made.

Equal Opportunity

All hiring, promotion, and other employment decisions remain merit-based and free from discrimination on the basis of race, color, religion, religious creed, national origin, ancestry, age, sex, sexual orientation, gender, gender identity, gender expression, physical disability, mental disability, pregnancy, medical condition, genetic information, marital status, citizenship status, military status, veteran status, or any other characteristic protected by federal, state, or local laws.
In addition, AT&T will provide reasonable accommodations to qualified individuals with disabilities.