Lead Advanced Analytics

AT&T•Dallas, TX

19h•Onsite

About The Position

This role strategically analyzes data from diverse sources using advanced predictive modeling, statistical techniques, and trend analysis to drive informed decision-making and optimize business performance across the enterprise. The ideal candidate leverages AI-powered tools and agentic workflows to accelerate development, automate processes, and deliver intelligent solutions at scale. Recognized as an experienced professional and subject-matter expert who creatively resolves highly complex and ambiguous issues through deep technical and business knowledge. Leads major initiatives with significant strategic impact, influences executive-level decisions, implements long-term plans affecting the broader organization, and collaborates frequently with senior leadership.

Requirements

Bachelor's degree (BS/BA) from an accredited university in a quantitative field such as Data Science, Mathematics, Statistics, Engineering, or Physics
5+ years of related experience
Certifications required in certain specialty areas
Expertise in advanced analytics, statistics, and predictive modeling techniques
Experience with analytics and data platforms such as Tableau, Power BI (AI Insights), Databricks, AWS, Azure, Synapse, and H2O Driverless AI
Advanced Python skills (pandas, NumPy, PySpark) and advanced SQL (CTEs, window functions, query optimization)
Proficiency with AI coding assistants (Windsurf Cascade, GitHub Copilot, Cursor) and agentic AI frameworks
Hands-on experience with Large Language Models (OpenAI, Claude, LLaMA, Gemini) and prompt engineering
Experience building agentic workflows, RAG pipelines, and AI-powered automation
Experience with cloud data platforms: Snowflake (Snowpark, Cortex) and Databricks (Delta Lake, Unity Catalog)
Proficiency with Azure services: Data Factory, Synapse Analytics, ADLS, Azure ML
Experience with ML frameworks: MLflow, scikit-learn, XGBoost, PyTorch
Ability to synthesize complex data into clear, actionable insights for executive-level decision-making
Proven ability to influence outcomes across multiple organizations and lines of business
Strong GitHub skills, CI/CD pipelines, and DevOps practices
Excellent communication skills with the ability to convey technical concepts to executive audiences
Experience mentoring and guiding analytics professionals

Nice To Haves

Experience in Supply Chain, Procurement, or Finance analytics domains
Cloud certifications (Azure Data Engineer, Snowflake SnowPro, Databricks Certified)
Familiarity with enterprise AI governance and responsible AI practices
Experience with Snowflake Cortex, Databricks Genie, or similar cloud-native AI services

Responsibilities

Gather, analyze, and interpret diverse data sets to solve ongoing and emerging business problems, predict behaviors, and identify causal relationships, trigger points, and predictive outcomes.
Work with relational databases (e.g., Oracle, MySQL) and data warehouse technologies (e.g., Snowflake, Databricks Delta Lake), leveraging internal and external data sources including data lakes and enterprise data warehouses.
Use a broad range of advanced statistical techniques to quantify data variances and support data-driven decision-making through traditional and advanced modeling methodologies.
Build, test, and validate predictive models using real-world data samples, including linear regression, logistic regression, and time-series modeling.
Develop business cases and complex analytical models using big-data analytics and visualization tools such as Tableau and Power BI, to recommend improvements to business processes, financial outcomes, and operating models.
Create dashboards, reports, and visual analytics that clearly communicate insights to business partners.
Advise stakeholders on patterns, relationships, and trends in data to inform strategic direction, performance improvements, and business outcomes.
Lead significant, high-impact analytics initiatives with strategic autonomy, collaborate closely with senior leadership, and mentor less experienced team members.
Use AI-powered development environments (e.g., Windsurf Cascade, VS Code with GitHub Copilot, Cursor) to accelerate coding, debugging, testing, and documentation.
Design and build agentic AI workflows using frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, and Semantic Kernel.
Implement RAG (Retrieval-Augmented Generation) pipelines using vector databases, embeddings, and document retrieval techniques.

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
Comprehensive benefits package
Career development resources