About World Business Lenders
(www.wbl.com)World Business Lenders (WBL) is proud to offer short-term, real estate-backed commercial loans to a diverse range of small and medium-sized businesses across the United States, especially those who may find it challenging to secure traditional financing.Typically, the work schedule is from 9:00am to 6:00pm Eastern Time, Monday through Friday, though there might be times when additional hours are needed to meet business demands.We’re looking for someone with strong communication skills in both English, both spoken and written.Please note that all resumes should be submitted in English.About the roleThis 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 (e.g., lead scoring, conversion propensity, and forecasting) into actionable insights. In parallel, this individual will support internal data science and modeling efforts, contributing to the development of proprietary analytics capabilities. The role is expected to initially focus on marketing-related modeling and progressively expand into deeper data science work over time.This position requires a solution-oriented mindset — someone who takes ownership, challenges assumptions, and actively improves processes rather than simply executing tasks.Key Responsibilities:Develop, validate, and maintain predictive models including lead scoring, conversion propensity, and funnel optimizationDevelop tiering models to prioritize leads by conversion probabilityBuild forecasting frameworks for lead volume, conversion rates, and pipeline or revenue projectionsBuild channel performance models to optimize budget allocation across paid search, email, ISO partners, etc.Monitor model performance and iterate to improve accuracy and business impactDevelop models to evaluate and prioritize markets based on expected performance and ROIAnalyze geographic, industry, and segment-level trends to identify growth opportunitiesSupport data-driven recommendations on market targeting and resource allocationSupport campaigns/future product launches by forecasting lead volume, conversion rates, and CAC by channelDesign and analyze experiments (A/B testing, cohort analysis) and evaluate incremental impactApply statistical and machine learning techniques to solve marketing and business problemsConduct deep-dive analyses to support strategic and operational decisionsContribute to internal data science and modeling initiatives, including proprietary or internal IP workCollaborate with Data Engineering to structure and prepare datasets for modelingPartner with BI and analytics teams to ensure model outputs are integrated into reporting and usable by stakeholdersRequirementsRequired Education: Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, or related field.Required Experience:3 to 7 years of experience in data science, applied modeling, or advanced analytics.Required Background / Industry Experience:Strong proficiency in Python and SQLProven experience building and validating predictive models in a business environmentExperience with statistical methods, machine learning techniques, and forecasting approachesStrong problem-solving skills and ability to translate business problems into analytical solutionsAbility to communicate complex analytical concepts to non-technical stakeholders Experience with customer acquisition cost modeling and marketing ROI analysisPreferred:Experience working with marketing, customer acquisition, or lead generation dataFamiliarity with segmentation, lead scoring, or customer lifecycle modelingExperience with experimentation and causal inference methodsExposure to market-level modeling or customer targeting strategiesExperience contributing to production-level or internal data science projectsKey Soft Skills:Clear communication: can explain data issues, tradeoffs, and results to both technical and business stakeholders.Collaboration: works effectively across engineering, analytics, and business teams.Technical Skills:As stated under "Required Background / Industry Experience".BenefitsUSD Base Salary.Enjoy Paid Time Off (PTO) after just 6 months of service.Full-time opportunity.Enjoy the freedom of a completely remote work environment!
