Lead Data Scientist- Collections Campaign

Role Overview: Yubi, formerly known as CredAvenue, is seeking a skilled Lead Data Scientist to join their team and contribute to building Collection Campaign Recommendations/Optimizations. As a Lead Data Scientist, you will play a key role in designing, developing, and deploying ML/RL models to enhance and optimize collection campaigns across digital, telecalling, and field channels. Your expertise in machine learning, along with strong Python programming skills, will be instrumental in driving innovation and creating business value for clients. Key Responsibilities: - Develop, implement, and maintain advanced analytical models and algorithms focused on improving debt collection processes. - Collaborate with business stakeholders to identify opportunities for data-driven enhancements in debt collection strategies. - Continuously enhance existing models and integrate new data sources to optimize collection approaches. - Take ownership of the end-to-end process of metric design, tracking, and reporting related to debt collection performance. - Regularly refine and update metrics to align with business objectives and regulatory standards. - Effectively communicate findings to both technical and non-technical stakeholders. - Mentor, train, and support junior data scientists to foster a culture of continuous improvement and collaboration. - Lead cross-functional teams on data projects, ensuring alignment between data science initiatives and business objectives. - Stay updated on the latest industry trends, tools, and best practices in analytics and debt management. Qualifications Required: - Experience: 8 to 10 years - Technical Skills: - Profound understanding of machine learning algorithms and their application to risk assessment. - Expertise in statistical analysis, including hypothesis testing, regression analysis, probability theory, and data modeling techniques. - Proficiency in designing, developing, and delivering end-to-end data products and solutions. - Familiarity with model explainability techniques and regulatory compliance for risk models. - Strong proficiency in Python programming. - Working knowledge of PySpark (Good to have). - Ability to build and deploy models on cloud platforms such as AWS. - Proficiency in developing backend microservices using Fast API and knowledge of MLOps. - Experience with NLP techniques is a plus. - Domain Skills (Good to have): - Previous expertise in debt collection processes, credit risk assessment, regulatory compliance, and industry best practices. - Demonstrated ability to design, implement, and optimize performance metrics tailored for debt recovery initiatives. - Education and Experience: - Bachelors/Advanced degree in Data Science, Statistics, Mathematics, Computer Science, or a related field. - 5 to 8 years of experience in data science and machine learning domain. - Experience in the financial sector or Collection team is advantageous.,