Roles & Responsibilities:
1. Collaborate with cross-functional teams including product managers, engineers, and business stakeholders to identify and define data science requirements for lending solutions.
2. Collect, clean, and preprocess large-scale structured and unstructured data from various sources to extract meaningful insights and build predictive models.
3. Perform exploratory data analysis to identify patterns, trends, and correlations, and translate them into actionable recommendations.
4. Conduct rigorous testing and validation of models, ensuring accuracy, reliability, and scalability in real-world lending scenarios.
5. Drive end-to-end model deployment, working closely with software engineers to integrate models into production systems and monitor their performance.
6. Continuously monitor and evaluate model performance and provide insights for model refinement and improvement.
7. Stay up-to-date with the latest advancements and research in data science, machine learning, and lending industry trends, and apply them to enhance our lending strategies.
8. Mentor and provide feedback to team members
Preferred Qualifications:
1. Proven experience in applying data science techniques and machine learning algorithms to solve complex problems in the lending domain.
2. Expertise in managing the entire lifecycle of complex machine learning projects, including development, implementation, and deployment of large-scale solutions
3. Proficiency in programming languages such as Python or R, and experience with data manipulation and analysis using libraries like Pandas, NumPy, and scikit-learn.
4. Strong knowledge of statistical analysis, regression modeling, and predictive modeling techniques.
5. Experience with big data frameworks (e.g., Hadoop, Spark) and cloud-based data technologies (e.g., AWS, Azure) is desirable.
6. Familiarity with SQL and database systems for data extraction and manipulation.
7. Excellent problem-solving and critical-thinking abilities, with a keen attention to detail.
8. Strong communication skills, with the ability to explain complex concepts and insights to both technical and non-technical stakeholders.
9. Prior experience in the fintech industry or lending domain is a plus.
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