Data Scientist

About the Company

TVS Credit Services Ltd is a part of the $8.5 billion TVS Group, dedicated to empowering individuals across India by providing timely and affordable financial credit to help them achieve their aspirations. Operating across diverse socio-economic segments, TVS Credit offers various financial products such as Two Wheeler Loans, Used Car Loans, and Business Loans. With a customer base exceeding 13 million and a strong CRISIL rating of AA, the company emphasizes financial inclusion and innovation through advanced technology and analytics. It has garnered numerous accolades including the Economic Times Best BFSI Brand and the NBFC Leadership Award.

Role Overview

The role’s central focus is cultivating a strong data aggregation and analytic culture to enhance consumer experience and organizational data utilization. This includes recognizing patterns in data and leveraging insights to drive strategic decisions.

Key Responsibilities

• Expand and oversee the organization's analytics capabilities across different departments and guide strategy aligned with analytics goals.
• Manage the organization and examination of extensive and varied datasets spanning multiple platforms.
• Extract critical insights to influence and shape product strategies effectively.
• Engage technically with vendors and partners to define scope, approach, and ensure deliverables meet expectations.
• Create proofs of concept to validate or invalidate ideas and hypotheses.
• Collaborate with various business units to assess analytic requirements and develop methods for accurate, efficient, and relevant reports.
• Design and execute advanced statistical tests tailored to specific problem-solving needs.
• Communicate succinctly and clearly analytical findings to senior leadership, translating results into actionable strategic recommendations.

Candidate Requirements

• Possess an MTech, BE, BTech, or MSc degree in Computer Science, Statistics, Mathematics, Operations Research, Econometrics, or any related quantitative discipline.
• Have a minimum of 4 years of experience working in analytics or a related field.
• Demonstrate strong analytical thinking, logical reasoning, problem-solving aptitude, and numerical skills.
• Proficient in programming with Python.
• Experienced in handling large datasets and operating in big data environments using tools such as SQL, Hadoop, and Hive.
• Show a strong passion for large-scale data analysis and the aptitude to discover meaningful insights.
• Expertise in machine learning algorithms including but not limited to XGBoost and Support Vector Machines (SVM).
• Well-versed in various data mining and statistical methods, including regression analysis, logistic regression, segmentation, time series forecasting, market basket analysis, decision tree analysis, CHAID, text mining, hypothesis testing, A/B testing, and predictive modeling.