Sr. Specialist, Marketing Measurement & Analytics

Key Responsibilities

Design, Build & Support Complex Datasets

• Support the connection, structuring, and preparation of datasets from various stakeholders.
• Assist with configuring API connections and automated data pipelines.
• Write and optimize SQL queries to support efficient data processing.
• Help maintain and improve the data warehouse environment.
• Use AI tools (LLMs, Workflows, Automation) for data cleaning, modelling, and workflow improvement.
• Explore predictive or automated techniques (e.g., AI powered insight generation, anomaly detection, trend flagging, classification logic) alongside team members.

Enable Data-Driven Storytelling & Visualization

• Work with Marketing teams across regions to help turn complex datasets into meaningful insights.
• Build dashboards, reports, and visualizations in Domo/Tableau that support day-to-day decision-making.
• Provide training and support to stakeholders on dataset usage and visualization best practices.
• Apply AI-powered capabilities (e.g., automated narratives, data summarization, pattern recognition) to enhance dashboards and insight delivery.
• Use LLMs to speed up documentation, metadata creation, and initial drafts of analyses.

Support Holistic, AI-Enabled Insight Generation

• Contribute to structured analysis aligned with key business priorities.
• Assist in introducing new techniques leveraging machine learning or AI, working closely with senior analysts to test and apply them appropriately.
• Support ongoing improvement of methodologies for defining and calculating Marketing ROI.
• Stay aware of evolving analytics technology, including new AI tools, and flag opportunities for the team to adopt or experiment with them.

Basic Qualifications

• ~3+ years of experience in a data-driven environment, ideally supporting BI, ETL, or analytics workflows.
• Strong foundation in data manipulation, SQL, and analytical thinking.
• Bachelor's degree in Information Systems, Statistics, Computer Science, Engineering, or equivalent experience.

Preferred Qualifications

• Exposure to Python, Java, or R (basic scripting skills a plus, but not required).
• Experience working with large datasets and applying basic statistical methods.
• Dashboard/visualization experience (Domo, Tableau, Power BI, etc.).
• Practical experience using AI tools (LLMs, copilots, generative AI) for analysis, automation, or productivity enhancements.
• Familiarity with predictive analytics or machine learning concepts (foundational knowledge is sufficient).
• Strong communication, collaboration, and project coordination skills.
• Ability to present insights in a clear and business-friendly way.
• Curiosity, problem-solving mindset, and interest in learning new technologies - especially AI.