Data Scientist. Cutting-edge machine learning to build products for the developing world that save lives.

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Groundbreaking AI for true social good.

Build and implement machine learning to shape an ambitious vision for the future of healthcare – save lives now and help shape the future of health at global scale. Our work is supported by the Bill & Melinda Gates Foundation, UNICEF, USAID and multinational organizations.

You will create transformative solutions the world has never seen. We are working on unsolved problems at the nexus of state of the art of machine learning and healthcare: the first predictive supply chain for health, a new model for understanding demand for immunization, computer vision and deep learning to automate ground-truth data collection and audit critical supply chains. Go beyond theory: what you build will become products, deployed across the developing world to determine how governments understand - and drive - demand for life-saving vaccination and prevent life-threatening outbreaks.

macro-eyes is working towards a future in which the delivery of care is predictive everywhere, where health systems anticipate health needs down to the individual and ensure the right resource is used at the right time, personalizing care, increasing access and maximizing efficiency. We believe that the first health system with AI at its core will be in the developing world. You will build the future.

macro-eyes is an AI company rebuilding the foundations of healthcare to make the delivery of care predictive everywhere. We have a mandate to deliver social impact, global presence and an international machine learning team led by MIT faculty. The macro-eyes team has built and shipped cutting-edge machine learning systems that run in the wild at leading academic medical centers in NYC and California and at one of the largest heart hospitals in the US. macro-eyes is supported by the Bill & Melinda Gates Foundation, the Draper Richards Kaplan Foundation, and USAID and has partnered with Microsoft, Stanford, the Government of Tanzania, and the world's largest academic clinical research organization. Accenture spotlighted macro-eyes product Sibyl as critical digital health technology of the future.

Expected qualifications

Strong drive to use ML for social good, and solid background in Machine Learning. Statistics and experience working with messy data a plus. Python fluency needed. Demonstrated ability to make meaningful contributions to projects with a research flavor is valuable. The successful candidate will be excited by the fact that the work we will do together is largely without precedent.

If this challenge is intriguing, please get in touch with benjamin@macro-eyes.com

Experience/Abilities:

  • hands on experience building predictive models

  • Experience working with diverse data types including images and structured data

  • Experience programming in Python, and one additional language (R, C, C++, Java)

  • Aware of current best practices in machine learning

  • Knowledge of statistics, including hypothesis testing with parametric and non-parametric tests and basic probability

  • Experience building different deep neural network models is preferred

  • French and/or German language skills a plus

We believe in recruiting the best talent in the world, regardless of location. This role will be remote with the freedom to choose how and when to work. You will have access to your choice of hardware and a travel budget to interact with the distributed team in person. macro-eyes has a rigorously horizontal culture that values diversity of every kind.

macro-eyes is dedicated to building an inclusive workforce where diversity is valued.

macro-eyes is an equal opportunity employer. Every qualified applicant will be considered for employment.

macro-eyes does not discriminate based on race, color, religion, gender, gender identity or orientation, genetic information, age, national origin, marital status, disability status, political ideology, military or protected veteran status, or any other characteristic protected by applicable federal, state, or local law.