Director - Data Scientist

Responsibilities

• Build end to end DS/AI/ML solutions.
• Own analyses, model training, deployment, business impact A/B evaluation, and subsequent iterations, for best-in-class data science models.
• Primary focus on dynamic pricing and discounting modules for various lines of business (flights, hotels, domestic, international, B2C meta) and potentially other products of both brands MakeMyTrip and GoIbibo.
• Work with stakeholders at various stages of the project, lead project development.
• Conduct iterative experiments, demonstrating incremental lift in business metrics due to AI/ML initiatives.
• Improve the system quality with best-in-class models and engineering tech.
• Opportunity to work with large click stream e-commerce data sets, at MakeMyTrip, GoIbibo, and TripMoney FinTech.
• Build and own robust data science APIs meeting 99% SLA at very high RPS. Also, ensure training/inference MLOps rigour.
• Show business impact while having the opportunity to build best-in-class AI/ML models.
  

Requirements

• Bachelor's degree in CS, EE, Mathematics, Statistics, Engineering technical field, or equivalent practical experience.
• A minimum of 14-18 years of experience (minimum of 10 years with a Ph. D. ) in applied DS /AI/ ML.
• Production experience in AI/ML Modelling, Pricing, discounting, recommendation systems and personalization.
• Production experience in price elasticity modeling or causal uplift modeling with combinatorial optimization is a plus.
• Production experience in contextual bandits and off-policy reinforcement learning methods is big plus.
• Production experience in sequential/incremental learning systems is a plus.
• Preferably, has worked in e-commerce.
• Experience with applying machine learning techniques to big data systems (e. g., Spark or Spark SQL) with TB to PB scale datasets.
• If one has a Ph. D, it should be in a quantitative field with strong/relevant experience for the problems mentioned above.
• Keen aptitude to learn and experiment with AI/ML adoption across various use cases.
• Experience with large-scale A/B testing systems, especially in the domain of online advertising or online commerce.