Measurement Lead

As Kard’s Measurement Lead, you’ll own and evolve how we showcase the impact of our work to both merchant and issuer partners. This includes designing and executing experiments, creating attribution and incrementality models, and providing actionable insights to both internal stakeholders and external clients. This high-impact individual contributor position is part of the Data team, collaborating closely with Go-To-Market (GTM), Product, Data Science, and Engineering teams to integrate top-tier measurement directly into our platform and workflows, ultimately driving strategy and optimizing results.

Responsibilities

• Design and implement incrementality and attribution frameworks to measure program impact.
• Run experiments and lift studies using rigorous causal inference techniques.
• Build reusable methodologies and playbooks for measuring performance across campaigns and partners.
• Deliver experimental results and actionable insights to clients.
• Partner with GTM teams to educate and advise customers on measurement best practices.
• Collaborate with Product, Engineering, and Data Science to integrate measurement and experimentation tools into our platform.
• Analyze performance trends, uncover insights, and inform strategy and product direction.
• Advocate for transparent, business-relevant measurement across the organization.
• Continuously improve internal processes for campaign analysis, test design, and reporting.
• Stay current with industry and academic advances in marketing measurement and experimentation.

Desired Skills

• 5–8 years in marketing measurement, experimentation, or analytics, ideally in adtech, martech, fintech, or marketplaces.
• Expertise in causal inference, experimentation design, and attribution methods, including randomized controlled trials, pre/post analysis, synthetic controls, and matched markets.
• Proficiency in SQL and Python, with experience analyzing large datasets.
• Ability to communicate complex statistical concepts and business-impactful insights clearly to technical and non-technical audiences.
• Familiarity with attribution models (e.g., last-touch, multi-touch, algorithmic) and lift testing frameworks
• Experience collaborating with revenue-facing teams and advising partners.
• Strong written, verbal, and data visualization skills.
• Bachelor’s or Master’s in Statistics, Economics, Computer Science, or related field.
• Curious, collaborative, humble, and business-minded with a bias for action.
• U.S. core business hours availability and willingness to travel for company meetings.