✨ About The Role
- Develop time-dependent statistical and ML models to solve product needs across various verticals like supply/demand matching, support prediction, and infrastructure auto-scaling
- Own the modeling life cycle end-to-end, including feature creation, model development, prototyping, monitoring, and maintenance
- Contribute to the development of an in-house Forecasting Self-Service Platform and proprietary Forecasting Repository to enhance capabilities
- Research new tools within the Forecasting space to stay updated on advancements like TimeGPT and LLM extensions
- Work with a team of engineers, analysts, and product managers to develop and iterate on models that impact millions of users and tackle challenging business problems
âš¡ Requirements
- Experienced in developing advanced statistical and machine learning models in a production environment, with at least a Master's degree and 3+ years of experience or a PhD and 1+ year of experience
- Proficient in object-oriented programming and various ML libraries such as Python, SciKit Learn, Lightgbm, Spark MLLib, PyTorch, and TensorFlow
- Deep understanding of complex systems like Marketplaces and domain knowledge in areas like Machine Learning, Causal Inference, Operations Research, and Forecasting
- High-energy individual who is driven, focused, and takes ownership of their work, while being adaptable, resilient, and able to thrive in ambiguity
- Growth-minded and eager to expand skill set in a hyper-growth setting, with a desire for impact and collaborative work within a team