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Sr. Data Scientist, Generative AI Applications




February 29, 2024

About the organization


Harvard University

Organization type

Academic Institution

In A Nutshell


Hybrid Boston, Massachusetts, USA



Job Type


Experience Level


Visa Sponsorship

Not Available

Deadline to apply

February 29, 2024

Create data science, machine learning, and AI solutions to better address the needs of Harvard Business School’s constituents (students, alumni, faculty, researchers, staff, and community at large).


  • Develop analytical models and solutions / production-ready algorithms that solve real business problems, taking into account business needs and technology/operations landscape; lead interaction with internal stakeholders and technology on specific projects and initiatives.
  • Apply data science, machine learning, and AI techniques to derive business value from the full range of internal and external data sets in a cloud environment.
  • Build data science pipelines from feature generation, data visualization and models evaluation; design the solution, build initial code and provide documentation with ways of working to maximize time to value and re-usability.
  • Translate complex data and methodology into strategic, operationally feasible insights and recommendations; automate implementation.
  • Communicate clearly and effectively to technical and non-technical audiences, verbally and visually, to create understanding, engagement, and buy-in.
  • Identify trends and opportunities to drive innovation, both in what we do and how we do it; evaluate new data science, machine learning, and AI technologies and tools that can boost team performance, innovation and business value.
  • Embody the values and passions that characterize Harvard Business School, with empathy to engage with colleagues from a wide range of backgrounds.
  • Promote data science, machine learning, AI, and digital and emerging technologies at Harvard Business School in relevant channels through community engagement, networking, speeches, and publications as applicable.


  • Advanced degree in mathematics, physics, computer science, engineering, statistics, or an equivalent technical discipline.
  • Minimum of three years’ experience in developing machine learning models with a track record of creating meaningful business impact and working with multiple stakeholders.
  • Minimum of five years’ experience with Python and SQL.
  • Experience with cloud computing platforms and tools (AWS, GCP, or other).
  • Expertise in multivariate statistical modelling (e.g. clustering, regression, principal components and factor analysis, time-series forecasting, Bayesian methods) and machine learning (Random Forest, KNN, SVM, boosting and bagging, regularization etc.)
  • Proficiency with data visualization tools (D3.js, R Shiny, Looker, Streamlit, or similar).
  • Experience operationalizing end-to-end machine learning applications.

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