×
Register Here to Apply for Jobs or Post Jobs. X

Senior Data Scientist

Job in Dallas, Dallas County, Texas, 75215, USA
Listing for: AT&T
Full Time position
Listed on 2026-07-18
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist, Data Engineering
Salary/Wage Range or Industry Benchmark: 139000 - 233500 USD Yearly USD 139000.00 233500.00 YEAR
Job Description & How to Apply Below

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.

Overall

Purpose:

This role will co‑own critical AI deliverables for AT&T Finance Operations, supporting Treasury/Payments, Billing Operations and Corporate Financial Planning deliverables. Significant experience with these partners, their KPIs, processes and business challenges is preferred.

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 to drive informed decision‑making and innovation.

Key Roles and Responsibilities:
  • 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, Sci Kit Learn , Pandas, PyTorch, Tidy Verse, 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 Work spaces 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: An…

Position Requirements
10+ Years work experience
To View & Apply for jobs on this site that accept applications from your location or country, tap the button below to make a Search.
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).
 
 
 
Search for further Jobs Here:
(Try combinations for better Results! Or enter less keywords for broader Results)
Location
Increase/decrease your Search Radius (miles)
0
200
Filters
Education Level
Experience Level (years)
Posted in last:
Salary