Key Responsibilities
- Develop, implement, and maintain advanced analytical models and algorithms specifically geared toward improving debt collection processes.
- Collaborate with business stakeholders to identify key opportunities for data-driven improvements in debt collection strategies.
- Enhance existing models and incorporate new data sources to continuously optimize our approach.
- Own the end-to-end process of metric design, tracking, and reporting related to debt collection performance.
- Continuously improve and update metrics to align with business objectives and regulatory requirements.
- Communicate findings effectively with both technical and non-technical stakeholders.
- Mentor, train, and support junior data scientists, fostering a culture of continuous improvement and collaboration
- Lead cross-functional teams on data projects, ensuring alignment between data science initiatives and business goals
- Stay abreast of the latest industry trends, tools, and best practices in analytics and debt management.
Technical Skills
- In-depth understanding of machine learning algorithms (supervised, unsupervised, and ensemble methods) and their application to risk.
- Expertise in statistical analysis, including hypothesis testing, regression analysis, probability theory, and data modeling techniques, to extract insights and validate machine learning models.
- Experience in designing, developing, and delivering end-to-end data products and solutions.
- Expertise in model explainability techniques (e.g., SHAP, LIME) and regulatory compliance for risk models.
- Strong proficiency in Python.
- Working knowledge of PySpark ( Good to have )
- Proficiency in building and deploying models on cloud platforms (AWS).
- Proficiency in developing backend microservices using Fast API and working knowledge of MLOps.
- Experience with NLP techniques is good to have
Domain Skills ( Good to have )
- Prior domain expertise in debt collection processes, including credit risk assessment, regulatory compliance, and industry best practices.
- Proven ability to design, implement, and optimize performance metrics and key performance indicators tailored specifically for debt recovery initiatives.
Education and Experience
- Bachelor/Advanced degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
- 5 to 8 years of experience in the data science and machine learning domain
- Experience in the financial sector or Collection team is a bonus.
