Key Responsibilities: 1) Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making 2) Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data driven decision-making 3) Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc. to analyze data and uncover meaningful patterns, relationships, and trends 4) Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation 5) Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc. and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness Desired Experience (Minimum Requirements) " Professional Experience: 5+ years of experience in a Data Science role, with a proven track record of delivering models that impact business outcomes. " Experimental Design: Lead the design and analysis of large-scale experiments (A/B testing, multivariate testing) to validate hypotheses and measure the impact of product changes.