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Data Scientist

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CARS24

What drives us? Imagine: a single tap on your phone unlocks a world that transforms your entire car ownership journey, covering every milestone - from finding your perfect match to keeping it running smoothly, to selling it later. That's the future we're building at CARS24 Financial Services. Our mission is to ensure car ownership is stress-free. We want our customers to focus on the open road, not roadside worries. We're building a one stop shop - a Super App for all their car needs, powered by technology, data science, and deep customer insights, We are already one of the largest Autotech companies in the world, but we are not stopping here. We aim to grow 10x in the next five years. What will you drive? As a member of Collection Models Data Science team, you would be focused on gathering, analyzing, and utilizing data to improve collections, whether for debt recovery, customer engagement, or business insights. You will be exposed to activities ranging from (but not limiting to) model development, evaluation, validation, monitoring, implementation testing and documentation. You will have an opportunity to learn industry best practices in credit models development and will also be working on experimental models using machine learning techniques. You will also own the models and be a SPOC for all assessment by Risk Management team. Essential Responsibilities: Credit risk model development using traditional logistic regression and machine learning techniques Work closely with collection managers to define models for prioritizing collections efforts. Detailed documentation of the model development activity for review from Risk Management Challenging the existing procedures to bring in more efficiency to the model development process Preparing project presentations for review of Senior Management Evaluate various business problems across credit function and proposing model-based solutions Mentoring the junior members in the team for day-to-day activities Work closely with Cars’24 portfolio teams to understand changes in model performance Work on multiple projects and perform other duties and/or special projects as assigned. Provide analytic support on key business initiatives and develop a strong working knowledge of the data warehouse and applicable analytic data systems. Work independently with stakeholders and propose insights for decision making What are we looking for ? Masters /Bachelors Degree in Mathematics/Statistics, Operations Research, Economics, Computer Science/Engineering. 8-10 years relevant analytical experience in Scorecard development, ML modelling, Segmentation and Clustering. Minimum 2 years- experience in Consumer Credit. Must have at least 2 years hands on experience in building credit models using SAS or Python. Working knowledge of Logistical/Linear/Regressions CHAID/CART/Clustering techniques. Experience working in Hadoop and Bigdata environments. Possess strong coding skills in Python and Pyspark. Ability to decipher complex data and effectively present and communicate in a clear and concise manner Strong written/oral communication skills and ability to manage multiple projects simultaneously . Classical statistical techniques: Regression, Logistic regression, Clustering, Dimensionality reduction techniques, Machine Learning algorithms: KNN, NBM, DT, CART, Boosting & Bagging models, SVM, Neural net, Ensemble models etc. Desired Characteristics: Working knowledge of credit bureau/Banking or any alternative data Work experience in a financial institution or bank Development of Consumer risk models Systems Implementation experience.

Data Scientist

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