Senior/Staff Data Scientist, Consumer Apps - Klover

What you'll do

• Develop ML and statistical models for the earned wage advance product
• Build and improve predictive models for consumer decisioning, behavior modeling, fraud, churn, transaction intelligence, and other business-critical use cases
• Own full model development lifecycle: data exploration, feature engineering, model training, validation, deployment, monitoring, and retraining
• Develop reusable modeling pipelines, analytical tools, and production-quality code
• Apply statistical and mathematical judgment to model evaluation, calibration, robustness testing, and business impact measurement
• Collaborate with data analysts, engineers, product managers, and business stakeholders to deliver ML models
• Identify new opportunities for data science, predictive modeling, and optimization to improve product and business outcomes

Requirements

• 5+ years of direct experience as a Data Scientist, Machine Learning Scientist, Model Developer, Applied Scientist, Economist, or similar role
• Master's or Ph.D. in STEM field such as Computer Science, Statistics, Economics, Mathematics, Engineering, Physics, Operations Research, or related quantitative field preferred
• Ability to apply critical thinking, causal inference, abstract reasoning, and generalization to complex business and technical problems
• Expertise in developing, validating, deploying, and monitoring machine learning models in production
• Experience with AI/ML-assisted development tools and MLOps practices, including working with LLMs or autonomous agents
• Experience with predictive modeling, consumer behavior modeling, risk modeling, credit decisioning, fraud modeling, churn modeling, or other applied ML use cases
• Strong foundation in statistics, probability, mathematics, and machine learning fundamentals
• Strong Python coding skills for building models, pipelines, and analytical tools
• Strong SQL skills and experience with large, messy datasets
• Experience with feature engineering, model evaluation, calibration, monitoring, retraining, and diagnostics
• Experience with cloud computing services or platforms, preferably GCP
• Familiarity with version control, peer code review, and collaborative software development
• Ability to learn new technologies and modeling approaches quickly
• Willingness to work across data science, analytics, modeling, and technical execution
• Strong written and verbal communication skills for technical and non-technical audiences

Tech stack