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Senior Data Scientist (Credit)

Mission Lane

Full remote Today via WTTJ

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About the role

Join our team as a Senior Data Scientist, where you will innovate and improve machine learning models that drive efficient and accurate financial decisions. Collaborate with business leaders and technical experts to develop new data sources, enhance modeling methodology, and apply models with sound risk management. Enjoy a supportive work culture, comprehensive benefits, and opportunities for advancement. Key missions: Collaborate on designing, developing, and deploying machine learning models to solve practical problems and help our business and customers reach their financial goals.. Partner with business leaders and technical experts across the company to develop new data sources, improve our modeling methodology, and apply models with sound risk management.. Share best practices for software engineering and help smart, experienced data scientists with complex technical problems, especially operationalizing and evaluating models for real-world applications. Profile: - Has a BS / MS in a quantitative field and 3+ years of experience in a related role - You share best practices for software engineering and can help smart, experienced data scientists with complex technical problems - especially operationalizing and evaluating models for real-world applications - Considers themself a generalist data scientist more motivated by practical solutions than theoretical elegance - Is interested in a wide range of ML solutions, including established tools (e.g. Spark, Kubernetes, Airflow, MLFlow), emerging tools (like Chalk, BentoML, or DVC), and developing in-house tools - Practices solid fundamentals with software engineering (test-driven development, code review, refactoring) and the PyData stack (numpy, scikit-learn, pandas, etc.) - Has a PhD in a quantitative field and 1+ years of experience in a related role - Has collaborated on creating, deploying, and managing supervised learning models in production systems for vital applications - Experience managing a strong technical team - Experience building predictive models end to end - Experience solving problems in consumer lending or fintech - Interest in developing ways to train, interpret, and deploy neural network architectures for time series classification tasks

Scraped 7/30/2026