Senior Data Scientist

Verizon•Basking Ridge, NJ

4d•Hybrid

About The Position

As a Senior AI Scientist, you will drive profitable growth and business innovation by applying advanced machine learning techniques and cutting-edge AI technology. You will lead high-impact data science projects that revolutionize product personalization, marketing effectiveness, channel optimization, customer experience, and operational efficiency. Working closely with a team of data scientists, ML engineers, software developers, and business stakeholders, you will play a pivotal role in designing, building, and delivering next-generation AI/ML solutions. In this role, you will design and implement 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. Step into discussions with key business leaders to align data science initiatives with broader business strategies and identify new growth opportunities. Step into 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.
Four or more years of relevant experience required, demonstrated through work experience and/or military experience.
Foundational knowledge in mathematics, statistics, computer science, engineering, or a related quantitative field.
Experience developing and deploying AI agents end-to-end, with solid hands-on knowledge of LLMs, RAG, Google ADK, and LangGraph.
Demonstrated success leading large-scale data science or agentic framework projects from ideation through to production.
Hands-on programming experience in Python and SQL.
Experience with machine learning/deep learning algorithms, including Transformers, multi-agent frameworks, NLP, and expertise in using PyTorch and Scikit-Learn packages.
Familiarity with Git repositories, CI/CD pipelines, and standard version control workflows.
Experience with data platforms such as Spark, Hadoop, BigQuery, Snowflake, or Redis.
Experience with GCP, AWS, or other cloud computing services.

Nice To Haves

A Master's in Computer Science, Engineering, Data Science, or a related field.
Proven ability to leverage Hugging Face packages (such as CLIP) and apply the latest machine learning research from open-source repositories to real-world projects.
Background in traditional software development practices, web services (React, Django), and containerization (Docker).
Experience designing, optimizing, and scaling Recommendation and Ranking systems for telecom use cases.
Experience aligning multimodal parsing systems (PDF/image text extraction) with business offer execution pipelines.
Strong communication and interpersonal influencing skills.
Excellent problem-solving and critical-thinking capabilities.

Responsibilities

Design and implement agentic AI solutions to elevate the customer experience, optimize offer personalization, and automate complex customer queries.
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.
Oversee the end-to-end development and operational lifecycle, diving into root causes to solve complex technical challenges.
Step into discussions with key business leaders to align data science initiatives with broader business strategies and identify new growth opportunities.
Step into 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.