Lead Financial Analyst - AI

EchoStar•Littleton, CO

About The Position

The Finance AI Lead Analyst serves as an internal technical consultant and builder within the Retail Wireless Financial Planning & Analysis (FP&A) organization. Working at the intersection of Finance, Analytics, and Artificial Intelligence, this role accelerates AI adoption and resolves operational bottlenecks. It transforms financial modeling by establishing automated anomaly detection, custom GenAI workflows, and predictive analytics to reduce manual auditing effort. The role collaborates directly with FP&A and Data Engineering teams to optimize enterprise data pipelines and deliver secure, scalable, actionable financial insights. The analyst identifies high-value process improvements and designs, prototypes, and deploys AI solutions. The position enhances P&L modeling, recurring variance analysis, rolling forecasts, and strategic scenario planning using automated analytics; automates error checking, data validation, and anomaly identification; and upskills FP&A colleagues in prompt engineering and AI agent workflows while retaining human oversight. The role also partners with Data Engineering to define business requirements, integrate enterprise pipelines, and ensure AI-generated financial outputs are secure, accurate, and traceable. Candidates must be willing to participate in at least one in-person interview. Visa sponsorship is not available.

Requirements

Bachelor’s or Master’s degree in Finance, Data Science, or another quantitative field, or equivalent practical experience in financial technology or AI software development.
At least 5 years of experience across FP&A, Financial Analytics, Data Science, or AI Automation roles.
At least 5 years of experience with Generative AI models, LLM APIs, prompt engineering, and RAG architectures.
At least 5 years of experience using Python and SQL for data analysis and financial modeling.
At least 5 years of experience with business intelligence platforms such as Power BI or Tableau.
Hands-on experience developing and deploying Generative AI models, LLM APIs, prompt engineering, RAG architectures, and AI agents.
Strong SQL and Python skills for data analysis, financial modeling, and deploying automated analytical workflows.
Deep understanding of core FP&A workflows, P&L modeling, recurring variance analysis, and rolling forecasting.
Proven ability to take AI projects from business problem identification through prototyping, deployment, and user adoption.
Ability to build consultative partnerships across FP&A stakeholders, Data Engineering teams, and IT.
Willingness to participate in at least one in-person interview.

Responsibilities

Identify high-value process improvements and design, prototype, and deploy custom solutions using LLMs, AI agents, and machine learning.
Enhance P&L modeling, recurring variance analysis, rolling forecasts, and strategic scenario planning through advanced automated analytics.
Automate error checking, data validation, and financial anomaly identification to improve financial model reliability and streamline audit workflows.
Upskill FP&A team members in prompt engineering and AI agent workflows while maintaining human-in-the-loop oversight.
Partner with Data Engineering teams to define business requirements, integrate enterprise pipelines, and ensure AI-generated financial outputs are secure, accurate, and traceable.