Noopur Dhawan
About Noopur Dhawan
Noopur Dhawan is a Senior Machine Learning Engineer at Delivery Hero in Berlin, Germany, with over 8 years of experience in data science and machine learning.
Current Role at Delivery Hero
Noopur Dhawan currently works as a Senior Machine Learning Engineer at Delivery Hero in Berlin, Germany. In her role, she focuses on implementing sophisticated machine learning models aimed at optimizing and improving delivery services. Her extensive experience in data science and machine learning makes her a valuable asset to the company.
Previous Experience at Twilio
From 2020 to 2021, Noopur Dhawan was a Staff Machine Learning Engineer at Twilio. During her one-year tenure, she contributed to various machine learning projects, leveraging her skills in TensorFlow and PyTorch. Her work at Twilio focused on developing and deploying machine learning solutions, further refining her expertise in the field.
Roles at Grab
Noopur Dhawan spent nearly two years at Grab in Singapore, initially as a Data Scientist and later as a Senior Data Scientist for Grab Food. Between 2018 and 2020, she was integral in implementing machine learning models that enhanced operational efficiencies and service delivery. Her work contributed significantly to Grab's data-driven decision-making processes.
Educational Background and Certifications
Noopur Dhawan has a robust educational background in artificial intelligence and machine learning. She has achieved multiple certifications, including TensorFlow: Data and Deployment Specialization and DeepLearning.AI TensorFlow Developer Professional Certificate from Coursera in 2020. She has also completed specializations in Natural Language Processing and Data Science, among others. Her formal education includes a program in C++ Programming and Web Development from the Indian Institute of Technology, Kanpur.
Technical Expertise and Skills
Noopur Dhawan possesses a strong proficiency in implementing Learn To Rank models and advanced skills in BERT for natural language processing. She is well-versed in both TensorFlow and PyTorch, two prominent frameworks in the deep learning community. Additionally, she is skilled in Python and various databases, which she leverages in her role as a machine learning engineer.