Applied AI Analyst

Nymbus, Inc.

10h•Remote

About The Position

Nymbus (https://nymbus.com/) isn’t just a leader in fintech; we’re a community of innovators passionate about reimagining banking. Our award-winning modern core platform and cloud-based technology serve as the backbone for financial institutions eager to modernize and excel. Here, you won’t just be part of a tech revolution. You’ll be at the helm, driving change. You’ll fit right in if you’re a creative thinker who’s eager to reduce technical debt and increase agility for banks and credit unions. Our culture thrives on collaboration, integrity, and a client-first approach. We operate with an AI-first mindset across all aspects of our business, continuously improving our efficiency and increasing the value we deliver to clients. We’re looking for individuals who are intensely curious about emerging technologies and passionate about innovation. Your journey with us won’t simply advance your career; it will offer the chance to help shape an industry alongside like-minded professionals. We’re excited to consider you a key player in this transformative chapter. Thank you for considering a role with Nymbus. The Applied AI Analyst operates at the intersection of business, data, and AI to solve complex problems and drive measurable outcomes. This role partners with functional leaders to bring analytical rigor, structure, and AI-enabled solutions to high-impact decisions, workflows, and strategic initiatives. Applied AI Analysts do not operate in theory alone—they are hands-on builders and problem solvers who design, prototype, and deploy AI-driven approaches that improve efficiency, decision-making, and business performance.

Requirements

Strong analytical thinking and problem-solving ability
Ability to work with ambiguity and define structure
Experience applying AI tools (e.g., LLMs, automation tools) to real-world problems
Process design and optimization mindset
Clear communication and ability to influence stakeholders
Bias toward action, experimentation, and iteration

Responsibilities

Problem Structuring & Analysis
Break down ambiguous business problems into clear analytical frameworks
Develop insights that inform decisions across product, engineering, operations, and go-to-market functions
AI-Driven Solutions
Design and prototype AI-enabled workflows, tools, and use cases
Apply AI to improve efficiency, quality, and scalability of work
Identify and prioritize opportunities for automation and augmentation
Workflow & Process Optimization
Analyze existing workflows to identify inefficiencies, gaps, and bottlenecks
Redesign processes to improve speed, consistency, and outcomes
Implement repeatable, scalable solutions
Data & Insight Generation
Build models, dashboards, and frameworks that drive visibility into performance
Synthesize large volumes of structured and unstructured data into actionable insights
Reusable Asset Development
Create templates, playbooks, and tools that can be leveraged across teams
Turn one-off work into repeatable, scalable capabilities
Cross-Functional Partnership
Work across teams (Product, Engineering, Operations, Sales, etc.) to support high-priority initiatives
Translate between technical and business stakeholders