Internal AI Innovation Analyst

Kaseya Careers•Miami, FL

About The Position

Kaseya® is the leading provider of complete IT infrastructure and security management solutions for Managed Service Providers (MSPs) and internal IT organizations worldwide powered by AI. Kaseya’s best-in-breed technologies allow organizations to efficiently manage and secure IT to drive sustained business success. Kaseya has achieved sustained, strong double-digit growth over the past several years and is backed by Insight Venture Partners www.insightpartners.com), a leading global private equity firm investing in high-growth technology and software companies that drive transformative change in the industries they serve. Founded in 2000, Kaseya currently serves customers in over 20 countries across a wide variety of industries and manages over 15 million endpoints worldwide. To learn more about our company and our award-winning solutions, go to www.Kaseya.com and for more information on Kaseya’s culture. Kaseya is not your typical company. We are not afraid to tell you exactly who we are and our expectations. The thousands of people that succeed at Kaseya are prepared to go above and beyond for the betterment of our customers. Analyst, Internal AI Innovation Locations Accepted: Miami, NYC Kaseya is seeking an Analyst, Internal AI Innovation to help discover, shape, and deliver high-impact AI solutions across our finance and operations functions. This is a business-facing, high-visibility role, focused on driving measurable financial outcomes by applying modern generative AI and automation tools to real workflows. The ideal candidate is someone who thrives in ambiguity, enjoys blending strategy with execution, and is excited to be both a driver of Kaseya’s internal AI innovation and pioneer of its AI future.

Requirements

1–3 years of experience in corporate finance/FP&A, consulting, investment banking/PE, operations strategy, analytics, product/ops, or a similarly rigorous, fast-paced environment.
Bachelor’s degree in a business-related field (business administration, finance, accounting, economics) or technical field (computer science, engineering, data science).
Demonstrated passion for curiosity-driven experimentation, and the ability to speak to personal GenAI projects, favorite tools, and lessons learned.
Strong conviction in AI’s transformative potential and excitement about driving it forward.
An analytical foundation and comfort applying a financial lens to decisions (ROI thinking, cost/benefit tradeoffs, unit economics, and business cases).
A bias for action, comfort with ambiguity, and the ability to create structures where none exist.
Technical acumen: Practical knowledge of modern AI platforms, large language models, and MLOps concepts; experience with Python, SQL, Power BI, or data modeling tools is a plus (not required).
Excellent Excel skills; experience building models and turning messy data into defensible outputs.
Comfort working across stakeholders: you can listen, synthesize, and translate between business and technical audiences without losing the plot.
Strong communication and storytelling skills, including writing crisp docs, building clean PowerPoint presentations, and presenting key insights to leaders.
Best-in-class attention to detail and an unwavering commitment to accuracy.
Most importantly, the desire to learn and ability to adapt to new problems. This role intentionally covers a wide breadth of functional areas and departments. Working here, you will be encouraged to grow and learn a lot in a short time. This is a great role for someone looking to start their own business one day, or someone who wants to get a strong understanding of how everything within a business is tied together.

Nice To Haves

Experience with Python, SQL, Power BI, or data modeling tools is a plus (not required).

Responsibilities

Partner with finance and operations leaders to map processes and prioritize opportunities where AI workflows can deliver ROI, efficiency, and competitive advantage.
Translate ambiguous business goals into actionable AI programs with clear objectives, success metrics, data needs, solution logic, and rollout approach.
Rapidly build and iterate prototypes and MVPs (weeks, not months) using generative AI tools, low/no-code automation, and light scripting where helpful.
Run quick-turn pilots (typically 1–6 weeks): define baselines, test solutions, gather feedback, and iterate toward outcomes that hold up in the real world.
Quantify and track impact: build simple ROI models and scorecards (time, quality, cost, revenue) and communicate results in clear, executive-friendly narratives.
Drive adoption and change management through demos, training sessions, office hours, and stakeholder communications.
Partner with IT, Security, Legal, and Compliance to ensure solutions meet governance, privacy, data handling, and security standards.
Coordinate handoffs to Engineering/Data/BIS for scalable production implementations (requirements, testing notes, monitoring needs, and ongoing improvement plan).

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