Senior Data Scientist

Responsibilities

• Build, deploy, and maintain production-grade credit and fraud models that are foundational to our real-time decisioning platform and essential to portfolio profitability
• Own the full MLOps lifecycle-from feature engineering, model training, and experiment management to production deployment, performance monitoring, drift detection, and continuous optimization
• Architect and scale end-to-end ML pipelines, ensuring reliability, reproducibility, and seamless integration with core decisioning services
• Design robust model monitoring frameworks that enable tracing, profiling, explainability, and rapid root-cause analysis for production incidents or model degradation
• Partner with data science, risk, and engineering leaders to shape modeling strategy, improve credit policy, and strengthen fraud defenses in response to customer behavior and macroeconomic trends
• Drive continuous improvement of existing models, incorporating new data sources, advanced techniques, and rigorous validation processes
• Communicate complex model logic and insights to non-technical stakeholders, clearly linking modeling decisions to business outcomes and strategic priorities
• About You
• 5+ years of hands-on experience building and deploying machine learning models, with a strong grasp of the end-to-end modeling lifecycle from feature engineering to validation and productionization
• 5+ years of professional experience writing performant, maintainable Python code in a collaborative production environment, leveraging core data science libraries like pandas, numpy, xgboost, and scikit-learn
• 2+ Years of experience working on Credit or Fraud risk models
• Proficient in SQL for querying, transforming, and analyzing large datasets, and comfortable working across relational databases and cloud-based data platforms
• Strong understanding of data structures, algorithms, and software engineering principles, and apply them to build robust and scalable data solutions
• Bachelor's degree in a quantitative or STEM field (e.g., Statistics, Mathematics, Computer Science, Engineering) and demonstrate strong analytical and problem-solving skills in your work
• Location Requirement: This position requires regular in-person attendance at one of our two office locations (Richmond, VA or Arlington, VA). Candidates must already be located within a commutable distance to either location, as relocation assistance is not available at this time

Requirements

• Advanced technical and analytical background, ideally with a Master's or PhD in a quantitative or STEM field, and a strong understanding of probability, statistics, and predictive modeling algorithms (e.g., Boosting, Random Forests, Decision Trees, Bayesian models)
• Exposure to data and compute platforms such as Snowflake and Databricks
• Background in financial services or experience working in fast-moving, high-growth environments such as startups
• Experience with modern ML infrastructure and tooling, including MLOps frameworks (e.g., MLflow, BentoML), CI/CD automation, and model observability, monitoring, and lifecycle management
• Familiarity with large language models (LLMs ) and their deployment in production environments
• Why choose Koalafi: A career at Koalafi means opportunities to tackle exciting challenges every single day. We take pri

Benefits

Additional Information

At Koalafi, we believe in a world where no one has to put an important purchase on hold. That's why we're making it easier for more people to pay for big purchases over time. Retailers across the country rely on us to offer flexible lease-to-own financing to their non-prime consumers, while increasing sales and strengthening customer loyalty. Their 2M+ customers love us because we provide a flexible way for them to make payments and give them an opportunity to improve their credit. Our 200+ Koalafi teammates enjoy inspiring and challenging work that accelerates their careers. Interested in learning more about how we're transforming the financing experience and joining our team?

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