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Fundwell · 2 months ago

Lead Data Scientist

New York, NY

Full-time

Onsite

Lead/Staff

Fundwell is a modern business financing platform redefining how small and medium-sized businesses access capital. They are seeking an exceptional Lead Data Scientist to drive AI/ML innovation within their Technology team, focusing on architecting and deploying advanced AI/ML systems to transform their core business through intelligent automation and predictive insights.

Financial Services

Responsibilities

Lead the design, development, and deployment of production-grade machine learning models that automate and optimize critical underwriting processes, delivering measurable business impact

Conduct sophisticated exploratory data analysis and statistical modeling to uncover high-value opportunities across underwriting and customer operations

Analyze complex, multi-modal datasets—including financial records, commercial data, alternative data sources, and temporal patterns—to extract actionable intelligence and improve model performance

Develop automated monitoring systems to continuously track model accuracy, fairness, drift, and regulatory compliance

Collaborate with Engineering teams to integrate ML models into production systems, enabling autonomous real-time decision-making at scale

Evaluate and implement the optimal statistical and modeling approaches—from traditional techniques like logistic regression and segmentation to modern deep learning architectures—based on problem requirements

Champion a culture of experimentation, innovation, and continuous learning within the data science organization

Qualification

Machine LearningStatistical ModelingData AnalysisMLOps ToolsCloud PlatformsDeep LearningBusiness AcumenInnovationCollaboration

Required

Lead the design, development, and deployment of production-grade machine learning models that automate and optimize critical underwriting processes, delivering measurable business impact

Conduct sophisticated exploratory data analysis and statistical modeling to uncover high-value opportunities across underwriting and customer operations

Develop automated monitoring systems to continuously track model accuracy, fairness, drift, and regulatory compliance

Collaborate with Engineering teams to integrate ML models into production systems, enabling autonomous real-time decision-making at scale

Champion a culture of experimentation, innovation, and continuous learning within the data science organization

Deep expertise analyzing diverse data types—financial, commercial, behavioral, demographic, telephonic—across various formats including structured, unstructured, time series, and real-time streaming data

Strong command of the complete ML lifecycle from problem formulation through production deployment, monitoring, and iteration

Proficiency with modern ML frameworks, cloud platforms, and MLOps tools for building scalable AI systems

Proven track record selecting and applying advanced statistical and ML techniques—classification, regression, clustering, ensemble methods, neural networks—to drive business outcomes

Ability to balance technical sophistication with pragmatic delivery, knowing when to leverage state-of-the-art methods versus proven approaches

Strong business acumen with demonstrated ability to connect data science initiatives to revenue growth, cost reduction, and strategic objectives