Hybrid Lead Analyst

at dentsu Austria

• Job title: Lead Analyst
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: SQL
• Location requirements: Hybrid, Bengaluru, India

About the role

• Operations Intelligence Analyst supporting the application of AI/ML to optimize business processes at Merkle. Collaborating with data teams and operational stakeholders to identify and implement intelligent solutions.

Responsibilities

• 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
• Complete training in Power BI, SQL, and foundational analytics; actively build knowledge of AI/ML concepts, LLM capabilities, and how to evaluate intelligent service opportunities
• Meet with operations stakeholders to understand their challenges; translate those into analytical questions and potential intelligent service concepts
• Define metrics and dashboards that support both current decision-making and future AI initiatives; create specifications for the Data Engineer to implement
• Present analysis findings and AI opportunity assessments to stakeholders; explain trade-offs, feasibility, and expected value in business terms
• Stay current on AI/ML/LLM developments relevant to operational use cases; evaluate new tools, services, and capabilities; share learnings with the team
• Partner with the Data Engineer on implementation feasibility; work with Power Platform team on how intelligent features integrate with existing applications
• Actively build expertise in AI/ML concepts, prompt engineering, and intelligent automation patterns alongside foundational analytics skills

Requirements

• 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.

Benefits

• 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