511: Data Science for Private Investing — LIVE with Drew Conway
Oct 5, 2021
auto_awesome
Drew Conway, an expert in data science for private investing, discusses his work at Two Sigma. Topics include the R Conference, machine learning for hackers, team structure at Two Sigma, and audience Q&A. The episode delves into the evolution of the R Conference, the value of community involvement for data science professionals, the Venn diagram in data science, and the future of data science as an interdisciplinary discipline.
Collaborative learning in NYHackR community fosters professional growth and knowledge exchange.
Close collaboration between data science and investment teams enhances private investing processes at Two Sigma.
Data scientists are hired based on problem-solving abilities, signaling a shift towards specialization in data science roles.
Deep dives
Introduction of the Podcast Live Episode with Drew Conway
The episode features a live recording at the New York R Conference with Dr. Drew Conway, the Senior Vice President at 2 Sigma, discussing how data science is strategically applied to private investment decisions. Dr. Conway's extensive background includes co-authoring the book 'Machine Learning for Hackers' and co-founding a data science startup. The live episode highlights private investing processes, differences between public and private markets, and the value of data science in investing.
Formation of NY HackR Community and Impact on Data Science Learnings
Dr. Conway shares his early involvement in the NY HackR community during his graduate studies and highlights the collaborative learning and networking opportunities in the data science domain. He mentions the inception of the community, its evolution into the world's largest R community, and the significance of in-person interactions for knowledge sharing and professional growth. The discussion touches upon the community's impact on knowledge exchange and the value of hands-on learning experiences.
Integration of Data Science and Private Investing at 2 Sigma
Dr. Conway elaborates on the integration of data science and private investing at 2 Sigma by emphasizing the close collaboration between data science and investment teams. He explains the buddy system approach to facilitate alignment between these teams, ensuring shared understanding of key terms and project goals. The conversation delves into the challenges and opportunities of applying data science in private markets, emphasizing the importance of structured teamwork and mutual learning between data scientists and investors.
Data Science Hiring Criteria
When hiring data scientists, the focus is on their problem -solving approach rather than specific technical skills or experience in a particular industry. Candidates are assessed on how they think through data problems and approach measurement and modeling tasks creatively.
Future of Data Science
The future of data science involves a shift towards specialization within the field, such as data engineering and ML ops, to address the increasing complexity of data systems and the need for efficiency. Despite evolving roles, the core principles of asking the right questions, identifying relevant data, and applying suitable methods remain crucial for effective data science practice.