We believe we can help build a future for everyone.
- We aim to be daring, but humble: We look for bold ideas — regardless of structure and stage — and help them scale by pairing engineers with subject matter experts to build tools that accelerate the pace of social progress.
- We want to learn fast, but build for the long-term: We want to iterate fast and help bring new solutions to the table, but we also realize that important breakthroughs often take decades, or even centuries.
- Stay close to the real problems: We engage directly in the communities we serve because no one understands our society’s challenges like those who live them every day.
Our success is dependent on building teams that include people from different backgrounds and experiences who can challenge each other's assumptions with fresh perspectives. To that end, we look for a diverse pool of applicants including those from historically marginalized groups — women, people with disabilities, people of color, formerly incarcerated people, people who are lesbian, gay, bisexual, transgender, and/or gender nonconforming, first and second generation immigrants, veterans, and people from different socioeconomic backgrounds.
By pairing engineers with leaders in our education, science, and justice and opportunity teams, we can bring technology to the table in new ways to help drive solutions. We are uniquely positioned to design, build, and scale software systems to help educators, scientists, and policy experts better address the myriad challenges they face. Our technology team is already helping schools bring personalized learning tools to teachers and schools across the country and supporting scientists around the world as they develop a comprehensive reference atlas of all cells in the human body.
The Director of Data & Research Science will lead and manage Meta’s machine learning (ML) research and data science teams. Our primary focus is to help accelerate scientific discoveries in biomedical research by making and applying breakthroughs in biomedical natural language processing (NLP), knowledge representation and reasoning.
We believe that the complexity and scale of scientific knowledge is limiting how quickly researchers can understand, navigate and quickly make powerful connections across what is known to solve problems and generate hypotheses. This is one of the fundamental challenges hindering the rate of discovery in basic scientific research.
As the Director of Data & Research Science, you will play a pivotal role in tackling this challenge for the world’s biomedical researchers. Using state of the art ML & NLP techniques and models, you lead the team in solving as-yet-unsolved problems related to the generation of the knowledge graph, personalized recommendations and rankings, search, and building predictive capabilities. If you want to make a difference and help accelerate science with innovative research outcomes, join us!
- Lead the research science and data science teams, design and execute Meta’s product focused, applied research agenda using internal resources and external academic collaborations
- Lead the team in pragmatically applying new and existing Machine Learning/Natural Language Processing knowledge representation and reasoning techniques and models into a production knowledge graph at scale - and to power Meta’s product personalization and recommendations features using methods such as collaborative filtering and network science
- Lead the teams to empower data-informed decision making about Meta -- to understand product, growth & engagement; identify areas of opportunity; and impact on the acceleration of science.
- Collaborate with leadership, product managers, user experience researchers, software engineers and biologists to ensure a high quality experience for biomedical researchers
- Own the success of all ML models, e.g. disambiguation, predictions, recommendations, document structure, metadata extraction, entity mention extraction and resolution, entity-type assignment, relation extraction, chains of reasoning, collaborative filtering
- Advanced training in and strong knowledge of the fundamentals of ML and NLP (Ph.D. preferred in Computer Science, Math, Statistics, or related fields)
- Comprehensive knowledge of modern ML tools and techniques and current leading edge research
- Experience leading teams to develop advanced machine learning models in one or more of: Natural Language Understanding, Information Extraction from Text, Information Retrieval, Recommendations, and deploying at scale as part of a product
- Contributions to the research communities, including publishing papers at major recent Computer Science and Machine Learning conferences
- Comprehensive knowledge of modern machine learning and data science tools and techniques, with coding skills (e.g., in Python or R or Java) and in a major deep learning framework like Pytorch or TensorFlow
- Bonus: Experience in applying Deep Learning models for classification, retrieval, parsing and information extraction from scientific publications, preferably in the biomedical domain
- Bonus: Analytics experience -- building product intuition, solving problems using data, and providing practical business insight using data