Remote - Marketing Intelligence Analyst

About World Business Lenders

World Business Lenders (WBL) offers short-term, real estate-backed commercial loans to small and medium-sized businesses across the United States, especially those who may find it challenging to secure traditional financing.

About the Role

This role is responsible for developing predictive models and forecasting frameworks that support marketing performance, customer acquisition, and market targeting, while also contributing to broader internal data science initiatives. The position combines hands-on statistical modeling and machine learning with applied business problem-solving to drive more effective, data-driven decision-making. The role will work closely with BI and analytics partners to ensure alignment between predictive outputs and reporting, helping translate model results into actionable insights. This position requires a solution-oriented mindset.

Key Responsibilities

• Develop, validate, and maintain predictive models including lead scoring, conversion propensity, and funnel optimization
• Develop tiering models to prioritize leads by conversion probability
• Build forecasting frameworks for lead volume, conversion rates, and pipeline or revenue projections
• Build channel performance models to optimize budget allocation across paid search, email, ISO partners, etc.
• Monitor model performance and iterate to improve accuracy and business impact
• Develop models to evaluate and prioritize markets based on expected performance and ROI
• Analyze geographic, industry, and segment-level trends to identify growth opportunities
• Support data-driven recommendations on market targeting and resource allocation
• Support campaigns and future product launches by forecasting lead volume, conversion rates, and CAC by channel
• Design and analyze experiments (A/B testing, cohort analysis) and evaluate incremental impact
• Apply statistical and machine learning techniques to solve marketing and business problems
• Conduct deep-dive analyses to support strategic and operational decisions
• Contribute to internal data science and modeling initiatives
• Collaborate with Data Engineering to structure and prepare datasets for modeling
• Partner with BI and analytics teams to ensure model outputs are integrated into reporting and usable by stakeholders