Data Scientist -1

About Yubi

Yubi, formerly known as CredAvenue, is re-defining global debt markets by freeing the flow of finance between borrowers, lenders, and investors. We are the world's possibility platform for the discovery, investment, fulfillment, and collection of any debt solution. At Yubi, opportunities are plenty and we equip you with tools to seize it.

In March 2022, we became India's fastest fintech and most impactful startup to join the unicorn club with a Series B fundraising round of $137 million.

In 2020, we began our journey with a vision of transforming and deepening the global institutional debt market through technology. Our two-sided debt marketplace helps institutional and HNI investors find the widest network of corporate borrowers and debt products on side and helps corporates to discover investors and access debt capital efficiently on the other side. Switching between platforms is easy, which means investors can lend, invest and trade bonds - all in place. Our platforms shake up the traditional debt ecosystem and offer new ways of digital finance.

Spocto

• Debt recovery & risk mitigation platform
  So far, we have more than 17000 enterprises, 6200 investors, and lenders and facilitated debt volumes of over INR 1,40,000 crore.

Backed by marquee investors like Insight Partners, B Capital Group, Dragoneer, Sequoia Capital, LightSpeed and Lightrock, we are the-of-its-kind debt platform globally, revolutionizing the segment.

At Yubi, People are at the core of the business and our most valuable assets. Yubi is constantly growing, with 1000+ like-minded individuals today who are changing the way people perceive debt. We are a fun bunch who are highly motivated and driven to create a purposeful impact. Come join the club to be a part of our epic growth story.

We seek a skilled Data Scientist to join our team and help build “Collection Campaign Recommendations/ Optimizations”

As a Data Scientist, you will be key in designing, developing, and deploying ML/ RL models that experiments and optimizes the collection campaigns across digital,telecalling and field. Your experience in machine learning and strong Python programming skills will be crucial in driving innovation and business value for our clients.

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.
• Stay abreast of the latest industry trends, tools, and best practices in analytics and debt management.

Required Skills

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’s/Advanced degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
• Experience in the financial sector or Collection team is a bonus.
• 1 to 3 years of experience in the data science and machine learning domain

• 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