Job Details

LatentView Analytics is a leading global analytics and decision sciences provider, delivering solutions that help companies drive digital transformation and use data to gain a competitive advantage. With analytics solutions that provide a 360-degree view of the digital consumer, fuel machine learning capabilities, and support artificial intelligence initiatives., LatentView Analytics enables leading global brands to predict new revenue streams, anticipate product trends and popularity, improve customer retention rates, optimize investment decisions, and turn unstructured data into valuable business assets.

Responsibilities & Essential Duties:

• Design and deploy innovative approval, qualification, and segmentation strategies that maximize application approval rates while achieving credit loss targets

• Develop and maintain underwriting policies that define minimum acceptance criteria and policy declines for segments outside Mulligan's risk appetite

• Create statistically grounded credit limit assignment frameworks that optimize lifetime customer value while managing downside risk

• Design pricing and interest rate strategies, including testing frameworks, to ensure adequate loss coverage, strong borrower selection, and high customer take-up rates

• Optimize data collection strategies by balancing the information value of data against customer friction and operational cost

• Partner closely with the manual underwriting team to build a hybrid risk framework that integrates analytical strategies with expert manual review, ensuring consistent execution and continuous feedback loops. This would require innovative credit strategy tooling to create differentiated credit pathways for applications based on their profile, loan amount exposure and complexity of underwriting required

• Collaborate with Product, Engineering, and Data Science teams to design and deploy scalable infrastructure that enables rapid iteration and refinement of credit strategies

• Establish robust portfolio monitoring and reporting processes to track approval rates, credit performance, and risk metrics against expectations

• Apply a thoughtful, forward-looking approach to portfolio construction to ensure assets are resilient across economic cycles and attractive to debt investors on a risk-adjusted basis

• Incorporate macroeconomic trends and forward-looking risk signals into credit strategy to ensure ongoing relevance in evolving market conditions

Qualifications:

• 8+ years of relevant experience in commercial risk data science and credit strategy within a fintech or banking environment

• At least 3–4 years of hands-on experience designing, calibrating, and managing credit strategies for Merchant Cash Advance (MCA) products; prior MCA credit strategy experience is required

• Strong experience overseeing model deployment, execution, and monitoring within a production environment; ML Ops experience is highly preferred Master's degree in Data Science, Statistics, Economics, Finance, or a related quantitative discipline required

Education:

• Bachelor's degree in a related quantitative field such as Data Science, Statistics, Mathematics, Economics, Finance, or Engineering required.

• Master's degree in Data Science, Statistics, Economics, Finance, or a related quantitative discipline required.

At LatentView Analytics, we value a diverse, inclusive workforce and provide equal employment opportunities for all applicants and employees. All qualified applicants for employment will be considered without regard to an individual's race, colour, sex, gender identity, gender expression, religion, age, national origin or ancestry, citizenship, physical or mental disability, medical condition, family care status, marital status, domestic partner status, sexual orientation, genetic information, military or veteran status, or any other basis protected by federal, state or local laws.