"People’s Dreams... Have No Ends" - Strong background in data mining, machine learning and deep learning, with experience in techniques such as supervised and unsupervised learning, natural language processing, and time-series forecasting. - Experience in productionizing models and deploying models in a production environment - Experience with cloud-based platforms such as AWS, Azure, and GCP - Experience in programming languages such as Python, R, and SQL, and proficiency in using machine learning libraries such as PySpark,TensorFlow, PyTorch, scikit-learn, and Keras - Strong understanding of experiment design, descriptive statistics, inferential statistics and bayesian statistics - Experience with Big data technologies such as Hadoop, Spark, and Hive, and ability to work with large datasets - Strong ability to communicate complex technical concepts to a non-technical audience, including stakeholders, management, and cross-functional teams. - Strong problem-solving and critical thinking skills, and ability to apply machine learning techniques to real-world problems in a business context. - Strong ability to work in a team environment and lead a team of data scientists and engineers. - Experience with Agile development methodologies and project management.