Jason Risch
Partner at Greylock Partners
San Francisco Bay Area
Overview
Work Experience
Partner
2019 - Current
I focus on enterprise investments across cybersecurity, AI/ML, and cloud infra. Involved investments include: Seven AI, LlamaIndex, Kodem, Cribl, Bedrock, Predibase, and Blockaid. Greylock Partners backs entrepreneurs who are building disruptive, market-transforming consumer and enterprise software companies, including the teams at Facebook, LinkedIn, AirBnB, Workday, Palo Alto Networks, Okta, Abnormal Security, AppDynamics, Rubrik, and Figma.
Greylock Partners invests in entrepreneurs that focus on consumer and enterprise software companies.
Product and Investor
2018 - 2019
Founded by Dr. Andrew Ng, AI Fund is a startup studio that builds new AI companies from the ground up. I operated portfolio companies from inception to seed funding, including prototyping products, signing initial customers, and recruiting the founding team. Companies I started while at AI Fund include https://bearing.ai/ and https://www.credo.ai/. AI Fund's investors include Sequoia, Greylock, NEA, and SoftBank.
AI Fund is a VC firm made up of AI pioneers, operators, entrepreneurs, and investors, supported by LPs such as NEA, Sequoia and Greylock.
Management Consultant
2017 - 2018
Tech practice
McKinsey Growth Tech serves leading growth stage tech players, venture capital, and growth private equity
Business Operations
2016 - 2017
Focused on operationalizing changes to the house-purchasing process and optimizing pricing models to improve unit economics.
Opendoor is a real estate technology company that simplifies the process of buying and selling homes.
Raised $1,887,930,000.00 from BlackRock and Healthcare of Ontario Pension Plan (HOOPP).
Mayfield Fellow
2015 - 2016
Selected as one of twelve Fellows from Stanford University for intensive nine-month training program on developing a theoretical understanding, practical knowledge, and leadership skills related to growing startup technology companies
Data Science
2015 - 2015
Worked in Python and R to develop a recommendation system for events. Techniques included Latent Dirichlet Allocation for NLP topic modeling, collaborative filtering for implicit feedback, and time series analysis. Analyzed user behavior through Mixpanel, SQL, and Pandas.