CONTRACT ROLE

Remote, USA ~20-30 hours/week

Pay range: $60-85/hr. dependent on experience

About our client

Our client is one of the largest and fastest-growing companies in the fintech space, offering products that help members bank without unnecessary fees, access their money sooner, build their credit, and more.

Position Overview

Our client is looking to hire a Marketing Analytics contractor for their Growth team. This is a high-visibility marketing analytics role, working on advanced measurement, AI-enabled modeling, and executive-facing performance reporting. You'll partner closely with leaders to help shape how the team makes budget and channel investment decisions.

Examples of projects include:

• Use MMM, experimental, and quasi-experimental methodologies to estimate incremental impact and drive business outcomes.
• Manage marketing reporting and analysis for paid, owned, and integrated channels, and for performance across acquisition, activation, engagement, retention, and LTV.
• Translate complex analyses into clear and persuasive executive-level recommendations.
• Partner with Marketing, Finance, and Product leadership to inform budget allocation and investment strategy.
• Improve processes using AI - workflow automations, reporting, forecasting and modeling, etc.

Experience

• 6+ years of experience in marketing analytics or a related quantitative field.
• A results-oriented mindset with a bias toward action, clarity, and high standards.
• Exceptional stakeholder management skills and experience influencing senior leadership and cross-functional executives.
• A demonstrated record of using data to drive measurable business impact in a consumer-facing marketing team.
• Experience with brand and performance marketing and how marketing teams operate those functions.
• Experience leading and developing high-performing analytics teams, with a track record of elevating talent and building strong culture.
• Deep expertise in marketing measurement, including attribution modeling, media mix modeling, causal inference, customer lifetime value modeling.
• Strong SQL proficiency and experience working with large-scale data warehouses.
• Proficiency in BI and visualization tools (e.g., Looker, Tableau, PowerBI); experience improving data accessibility across organizations.
• Strong statistical foundation (e.g., hypothesis testing, predictive modeling, experimental design), experience with Python.