Senior Data Scientist, HBS AI Institute

Company Description By working at Harvard University, you join a vibrant community that advances Harvard's world-changing mission in meaningful ways, inspires innovation and collaboration, and builds skills and expertise. We are dedicated to creating a diverse and welcoming environment where everyone can thrive. The HBS AI Institute is a global research center that provides research-driven insights, accessible to anyone in the world, on using AI and digital technologies to advance business and society. Founded on the premise that AI technology is only half the answer and that businesses must also revamp their processes to harness AI’s potential, the Institute is made up of an unbiased, multidisciplinary team of researchers and scientists, business leaders, and entrepreneurs. Job Description Job Summary: As a Senior Data Scientist, you will be a key member of the HBS AI Institute's Data Science Team, working closely with Harvard Business School (HBS) faculty and researchers on research projects in the social sciences related to business and management, digital transformation, data science and artificial intelligence. Specifically, you will be working with HBS faculty to leverage AI and investigate its implications for business and society through experimental research. You will also play a role in developing and disseminating ML and AI-based tools for the research community. Because you will act as an expert guide and resource for researchers with a wide range of abilities and knowledge relating to data methodologies and emerging technologies, a substantial component of the role is effective communication about technologies. Additionally, the ability to learn new skills on the fly, to keep up with emerging technologies, and to transition comfortably among multiple ongoing projects of varying size and complexity, are all crucial. Job-Specific Responsibilities: Extract, clean, explore, and analyze data collected from various sources, including organizational data, public data, and experimental dataParticipate in the intake and assignment of projects in the HBS AI Institute Data Science TeamDesign and execute data science and AI experiments with partner organizations.Create and implement a variety of models and analyses and be able to extract insights and inform strategy from them.Create and maintain clear documentation of data files, modeling choices, rationale, results, and annotated code and readme files.Present and explain data science methods and findings to faculty, managers and other non-technical stakeholders at HBS AI Institute.Provide training and mentorship of other data scientists, research scientists, post-doctoral fellows, research assistants, and PhD students.Troubleshoot complex problems and device a strategy of seeking solutions in collaboration with other data scientists.Document and disseminate findings.Build trust and collaboration by being present on-site and engaging directly with colleagues and various constituents.Responsible for other duties as assigned. Qualifications Basic Qualifications: Minimum of seven years’ post-secondary education or relevant work experienceMaster’s or PhD in one of the following disciplines: Computational Sciences in either Physics, Biology, Neuroscience, Statistics, Applied Mathematics, Computer Science or another quantitative field Minimum of 5 years of experience in data science or related quantitative role.Experience with R, Python, SQL, and related languages.Experience with AWS (RDS, EC2, S3, etc.) preferred or with Azure or Google Cloud.Experience with supervised and unsupervised ML methods.Advanced Statistical Expertise: Extensive experience with statistical modeling and regression analysis, including hypothesis testing and causal analysis. Familiarity with LLM API use for research purposes. Additional Qualifications and Skills: Ability to handle multiple projects, stakeholders and demandsStrong team player with excellent verbal and written communication skillsExperience with data visualization toolsExperience prototyping products for research purpose