Principal Data Scientist

Verizon•Alpharetta, GA

2d•Hybrid

About The Position

As a Principal Data Scientist, you will drive profitable growth and business innovation by applying cutting-edge machine learning techniques and advanced AI technology. You will spearhead high-impact data science projects that revolutionize product personalization, marketing effectiveness, channel optimization, customer experience, and operational efficiency. Working closely with a talented team of data scientists, ML engineers, software developers, and business stakeholders, you will play a pivotal role in designing and delivering Verizon's next-generation AI/ML solutions. In this role, you will architect agentic AI solutions to elevate the customer experience, optimize offer personalization, and automate complex customer queries. You will develop predictive models to forecast customer behavior and business events, translating complex technical outcomes into strategic insights for partners across marketing, customer experience, and engineering teams. To ensure peak performance, you will oversee the end-to-end development and operational lifecycle, diving into root causes to solve complex technical challenges. Your sharp judgment, technical expertise, and ability to bridge the gap between business problems and technical solutions will directly impact our bottom line. Lead discussions with key business leaders to align data science initiatives with broader business strategies and identify new growth opportunities. Lead the design, development, and optimization of agentic AI, LLM, and machine learning/deep learning solutions. Partner with engineering teams to deploy models into production (both real-time pipelines and batch processing) and systematically track model performance. Serve as a subject matter expert on agentic development, machine learning and predictive modeling, providing technical guidance and mentorship to junior data scientists. Drive technical excellence through active research and the practical application of emerging theories, tools, and technologies.

Requirements

Bachelor’s degree or four or more years of work experience.
Six or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
Strong foundational knowledge in mathematics, statistics, physical sciences, engineering, or a related quantitative field.
Experience developing and deploying AI agents end-to-end, with solid hands-on knowledge of LLMs, RAG, LangChain, and LangGraph.
Hands-on programming experience in Python and SQL.
Experience in machine learning/deep learning algorithms, including Transformer, transfer learning, NLP using Pytorch and scikit-learning packages.
Experience with data platforms such as Spark, Hadoop, BigQuery, Snowflake or others.
Experience with GCP, AWS, or other cloud computing services.

Nice To Haves

A Ph.D. in Computer Science, Engineering, Data Science, or a related field.
Demonstrated success leading large-scale data science projects from ideation through to production.
Proven ability to leverage Hugging Face packages and apply the latest machine learning research from Git repositories to real-world projects.
Background in traditional software development practices and methodologies.
Experience developing agentic solutions with Google ADK
Experience designing and scaling Recommendation and Ranking systems.
Experience aligning marketing strategies with offer execution and measuring campaign effectiveness.
Strong communication and interpersonal influencing skills.
Excellent problem-solving and critical-thinking capabilities.

Responsibilities

Lead discussions with key business leaders to align data science initiatives with broader business strategies and identify new growth opportunities.
Lead the design, development, and optimization of agentic AI, LLM, and machine learning/deep learning solutions.
Partner with engineering teams to deploy models into production (both real-time pipelines and batch processing) and systematically track model performance.
Serve as a subject matter expert on agentic development, machine learning and predictive modeling, providing technical guidance and mentorship to junior data scientists.
Drive technical excellence through active research and the practical application of emerging theories, tools, and technologies.