Senior/Staff Data Scientist

Responsibilities

• Hands-on development of ML and statistical models at the core of our EWA product
• Build and improve predictive models across consumer decisioning, consumer behavior modeling, fraud, churn, transaction intelligence, and other business-critical use cases
• Own the full model development lifecycle, including data exploration, feature engineering, model training, validation, deployment, monitoring, and retraining
• Develop reusable modeling pipelines, analytical tools, and production-quality code to support scalable data science work
• Apply strong 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 with quality, efficiency, and precision
• Identify new areas where data science, predictive modeling, and optimization can improve product and business outcomes

Requirements

• 5+ years of direct experience working as a Data Scientist, Machine Learning Scientist, Model Developer, Applied Scientist, Economist, or similar role
• Strong expertise developing, validating, deploying, and monitoring machine learning models in production
• Solid foundation in statistics, probability, mathematics, and machine learning fundamentals
• Strong Python coding skills, with the ability to build models, pipelines, and analytical tools from scratch
• Strong SQL skills and experience working with large, messy, real-world datasets
• Experience with feature engineering, model evaluation, calibration, monitoring, retraining, and model performance diagnostics
• Experience with cloud computing services or platforms (GCP preferred)
• Familiarity with version control, peer code review, and collaborative software development practices

Nice-to-Haves

• Master's or Ph.D. in a STEM field such as Computer Science, Statistics, Economics, Mathematics, Engineering, Physics, Operations Research
• Experience with AI/ML-assisted development tools and MLOps practices, including LLMs or autonomous agents
• Experience with predictive modeling, consumer behavior modeling, risk modeling, credit decisioning, fraud modeling, churn modeling
• Demonstrated ability to learn new technologies quickly
• Strong written and verbal communication skills