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# Engr III Cslt-Data Science

- **Company:** Verizon Communications Inc.
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Data Analysis, Big Data, BigQuery, Computer Programming, Continuous Integration, Data Presentation, Python (Programming Language), Machine Learning, Rapid Prototyping Process, Microsoft Copilot, SQL Databases, Teradata SQL, GitHub Copilot, LangChain, Large Language Models, Llamaindex, Generative AI, Agentic-AI, Kubernetes, Information Technology, Machine Learning Operations, Claude, Data Pipelines
- **Published:** October 3, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pou9r2uefr

## About the Role

Your primary focus will be transforming traditional financial operations into a proactive, AI-driven organization. You are a hands-on builder who thrives at the intersection of core ML, cutting-edge GenAI, and business strategy. You have a knack for rapid prototyping and possess the communication skills required to explain the "why" and "how" of AI to business leaders., * Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field

 * Three or more years of relevant professional work experience.
 * Three or more years of experience practicing data science, AI engineering, or machine learning, with a strong focus on core AI/ML, GenAI, and Agentic frameworks.
 * Experience with all phases of end-to-end Analytics project, such as (but not limited to): Ingestion, Munging, Model Building, Validation, Operationalization, Monitoring
 * Strong programming proficiency in Python and advanced SQL.
 * Proven experience working within cloud platforms (Teradata/ GCP) and using tools like BigQuery for large-scale data processing.
 * Demonstrated experience in rapid prototyping and building solutions leveraging Large Language Models (LLMs) and AI tools (e.g., Claude, Copilot).
 * Hands-on familiarity with specific Agentic AI and orchestration frameworks (e.g., LangChain, LangGraph, LlamaIndex).
 * Exceptional data storytelling and communication skills, with a proven ability to translate complex technical concepts into confident financial business decisions.

Even better if you have one or more of the following:

 * Advanced degree (Master's) in Computer Science, Statistics, Data Science, or a related field.
 * Prior experience in the telecommunications industry specifically dealing with financial data, billing systems, FinOps, revenue assurance.
 * Experience in designing and deploying end-to-end MLOps and LLMOps pipelines.
 * A strong understanding of financial forecasting models, anomaly detection algorithms, and time-series analysis.

## Description

As a Consultant (Analytics) you will be a pivotal player in modernizing telecom financial operations. Bridging the gap between implementation and architectural strategy, you will design, develop, and deploy advanced AI/ML, Generative AI, and Agentic AI solutions tailored for the finance domain. Your work will transition complex financial workflows-such as Forecasting as a Service, Explainability framework, Funnel Forecasting, Customer Profitability etc., and also performing analyses that impact Bad Debt, Cash flow, Credit Score cut models, etc., among others-into automated, intelligent, and proactive systems.

You will own the end-to-end lifecycle of critical AI models while translating complex technical results into compelling business narratives for finance leadership.

 * Design and deploy core AI/ML and Generative AI solutions to optimize financial operations.
 * Build and orchestrate Agentic AI workflows to automate multi-step financial analysis and decision-making processes.
 * Utilize foundational models and AI assistants (e.g., Claude, GitHub Copilot) to rapidly prototype, iterate, and deliver agile AI solutions to meet dynamic business needs.
 * Engineer robust data pipelines and write complex SQL/BigQuery queries to extract and transform large-scale financial datasets using GCP and Python.
 * Act as a data storyteller-synthesizing complex AI/ML model outputs into clear, actionable, and prescriptive insights for non-technical finance stakeholders.
 * Design, develop, and optimize Artificial Intelligence, NLP, SLM/LLM solutions to diverse real-world problems.
 * Implement MLOps best practices to ensure continuous integration, deployment, and monitoring of financial AI models in production environments.
 * Driving data-derived insights across the business domain by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives.