Lead Data Scientist

AT&T; Dallas, Northern (TX, KY); Hybrid; USD 161,000 - 270,000; Full time

Benefits offered by this job

Medical/Dental/Vision coverage

401(k) plan

Tuition reimbursement program

Paid Time Off and Holidays

Paid Parental Leave

Paid Caregiver Leave

Adoption Reimbursement

Disability Benefits

Life and Accidental Death Insurance

Employee discounts

Job summary

AT&T is seeking a Lead Data Scientist to translate complex business problems into scalable data science solutions across the full AI workflow, including data extraction, feature engineering, model development, and deployment.

The role collaborates with cross-functional teams, emphasizes explainability and monitoring of models in production, and offers extensive perks and a path to impact across AT&T's data platforms.

Qualifications

• Master's degree in a quantitative field such as Data Science, Math, Statistics, Engineering or Physics.
• 5+ years of related experience.
• Certification is required in some areas.

Responsibilities

• Data Extraction and Preparation: collect data from various sources and ensure its quality.
• Coding Solutions, Algorithms and Feature Engineering: develop features and perform exploratory data analysis with Python/R/Scala.
• Model Development, Deployment and Optimization: build, evaluate, and deploy ML models with monitoring and retraining.
• Visualization and Collaboration: create visualizations and reports for stakeholders with cross-functional teams.
• Generative AI: develop and implement generative models and related techniques.

Skills

Data extraction

Data cleaning

Feature engineering

EDA

Model development

ML Ops

Python

R

Spark

Pandas

PyTorch

Education

Master's degree in a quantitative field

Certification in data science or related field

Tools

Databricks

VS Code

Scikit-Learn

TensorFlow

Keras

Pandas

PyTorch

Job description

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: 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, 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, hyperparameter 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

An experienced professional, recognized as an expert, creatively resolving complex issues with broad and in-depth knowledge. Leads significant projects with strategic autonomy, influencing executive decisions. Mentors less experienced staff, implements long-term plans impacting the organization, and frequently collaborates with senior leadership.

Supervisor: No

TCP Career Step Differentiator

Performs very complex data science work, builds complex business models, and makes recommendations that impact multiple organizations, lines of the business, etc.

Education/Experience

Master's degree (MS/MA) required from an accredited University in a Quantitative field of study such as Data Science, Math, Statistics, Engineering or Physics. 5+ years of related experience. Certification is required in some areas.

Our Lead Data Scientist earn between $160,900 - $270,400. 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

• 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

Weekly Hours

40

Time Type

Regular

Location

Atlanta, Georgia; Dallas, Texas; El Segundo, California

Salary Range

$160,900.00 - $270,400.00

AT&T and its subsidiaries are committed to equal employment 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. AT&T is a fair chance employer and does not initiate a background check until an offer is made. Click here to learn more or request an application accommodation here.