Develop working knowledge of Merkle's operational workflows, key metrics, data systems (Salesforce, Workday, Dynamics 365, Power Platform), and current AI/ML capabilities in our tech stack
Research and propose 3-5 areas where AI/ML could improve operational outcomes — predictive models, LLM-powered automation, intelligent recommendations — with clear business cases for each
Produce analyses that answer real business questions and influence the data foundations needed for future intelligent services
Partner with stakeholders and the Data Engineer to define requirements for at least 2 AI-enhanced capabilities, from problem definition through success metrics
Develop frameworks for how we assess AI/ML opportunities — feasibility, data readiness, expected value, build vs. buy considerations
Actively build expertise in AI/ML concepts, prompt engineering, and intelligent automation patterns alongside foundational analytics skills

Bachelor's degree in a quantitative field (Statistics, Mathematics, Economics, Engineering, Computer Science, Business Analytics, Data Science) or equivalent practical experience
Demonstrated ability to work with data — through coursework, projects, internships, or self-study
Genuine curiosity about artificial intelligence, machine learning, and LLMs — you follow developments in this space, you've experimented with AI tools, you know how to manage prompts, and you think about how these tools could be applied
Personal projects, coursework, or competitions involving ML; experimentation with tools like ChatGPT, Copilot, or other AI assistants for real tasks
Ability to write queries to filter, join, and aggregate data (or strong willingness to learn quickly)
Comfortable with Excel or Google Sheets for data manipulation and basic analysis
Strong written and verbal English; able to explain analytical and AI concepts to non-technical audiences.

Front-row seat to applying AI/ML to real business problems — not theoretical, but practical
Opportunity to shape how a global organization adopts intelligent services
Hands-on experience identifying, defining, and launching AI-powered capabilities
Mentorship from experienced architects and engineers
Dedicated learning budget for AI/ML training and certifications
Clear growth path — from Analyst to Senior Analyst to AI Product Manager or Data Scientist roles
Collaborative team culture that values curiosity, experimentation, and learning

Lead Analyst

Key skills