Overview Datavant is a data platform company and the worlds leader in health data exchange. Our vision is that every healthcare decision is powered by the right data, at the right time, in the right format. Our platform is powered by the largest, most diverse health data network in the U.S., enabling data to be secure, accessible and usable to inform better health decisions. Datavant is trusted by the worlds leading life sciences companies, government agencies, and those who deliver and pay for care. By joining Datavant today, youre stepping onto a high-performing, values-driven team. Together, were rising to the challenge of tackling some of healthcares most complex problems with technology-forward solutions. Datavanters bring a diversity of professional, educational and life experiences to realize our bold vision for healthcare. Datavant is looking for an enthusiastic and meticulous Data Scientist to join our growing team, which builds machine learning models for use across Datavant in multiple verticals and for multiple customer types. As part of the Data Science team, you will play a crucial role in developing new product features and automating existing internal processes to drive innovation across Datavant. You will work with tens of millions of patients worth of healthcare data to develop models, contributing to the entirety of the model development lifecycle from ideation and research to deployment and monitoring. You will collaborate with an experienced team of Data Scientists and Machine Learning Engineers along with application Engineers and Product Managers across the company to achieve Datavants AI-enabled future. You Will Play a key role in the success of our products by developing models for NLP (and other) tasks. Perform error analysis, data cleaning, and other related tasks to improve models. Collaborate with your team by making recommendations for the development roadmap of a capability. Work with other data scientists and engineers to optimize machine learning models and insert them into end-to-end pipelines. Understand product use-cases and define key performance metrics for models according to business requirements. Set up systems for long-term improvement of models and data quality (e.g. active learning, continuous learning systems, etc.). Qualifications Advanced degree in computer science, data science, statistics, or a related field, or equivalent work experience. 4+ years of experience with data science and machine learning in an industry setting. 4+ years experience with Python. Experience designing and building NLP models for tasks such as classification, named-entity recognition, and dependency parsing. Proficiency with standard data analysis toolkits such as SQL, Numpy, Pandas, etc. Proficiency with deep learning frameworks like PyTorch (preferred) or TensorFlow. Demonstrated ability to drive results in a team environment and contribute to team decision-making in the face of ambiguity. Strong time management skills and demonstrable experience of prioritising work to meet tight deadlines. Initiative and ability to independently explore and research novel topics and concepts as they arise.
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