About

Rohan Singh Rajput is a highly motivated and fast-learning Senior Data Scientist with a fascination for analytics, visualization, data cleansing, and preprocessing to extract meaningful features for the model. He is currently the Personalization Lead at Headspace Health, where he is responsible for building production-ready recommendation systems and administering A/B testing to evaluate real-world performance of Machine Learning models. With over 6.77 years of relevant experience, Rohan has developed and deployed impactful Machine Learning systems that fulfill the requirements within the resource constraint. He has experience in planning and provisioning A/B testing to determine the practical performance of models. Rohan is a graduate student from the University of Central Florida May 2017 batch and has worked with various organizations. He is looking for a full-time opportunity in Machine Learning and Data Science. At Headspace Health, Rohan collaborates with multiple internal product managers to integrate machine learning-based solutions to solve a business problem with conversions, explores opportunities, and analyzes hypothesis-driven initiatives with the available evidence. He formulates essential technical and business KPIs to measure the impact of machine learning-based solutions on products. Rohan has also managed and deployed content recommendation systems on the Databricks platform for large-scale distributed data processing, replacing a rule-based editorial legacy system with a machine learning model to improve user engagement with stat sig. He has also developed, deployed, and administered machine learning model A/B test tools in the company, delivering the post-experiment notebooks and decks to demonstrate the leadership team and product stakeholders about experiments’ impact. Rohan has also worked as a Data Scientist II at Ticketmaster and a Machine Learning Engineer at Owned Outcomes. At Ticketmaster, he developed deep learning-based natural language processing models for artists and events. He also delivered machine learning interpretability and model monitoring systems using latent factors of matrix factorization-based models using Python. At Owned Outcomes, Rohan collaborated with pharmacies and hospitals to create a model for predicting patient risk scores, factors using EHR, census data, and upgraded a rule-based model to an ensemble machine learning predictive model using regression and XGBoost. Rohan has a strong technical skill set, including expertise in recommendation systems, data science, research science, AWS, Databricks, Python, Terraform, deep learning, NLP, infra, Django, XGBoost, RabbitMQ, and backend development. He also holds a Master’s Degree in Computer Engineering from the University of Central Florida and a Bachelor's degree in