Data-driven VC: June Roundup
Where venture capital and data intersect. Every week.
👋 Hi, I’m Andre and welcome to my weekly newsletter, Data-driven VC. Every Thursday I cover hands-on insights into data-driven innovation in venture capital and connect the dots between the latest research, reviews of novel tools and datasets, deep dives into various VC tech stacks, interviews with experts, and the implications for all stakeholders. Follow along to understand how data-driven approaches change the game, why it matters, and what it means for you.
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READS & RESEARCH
“An Engineering Approach to VC” by Alexander Lange from Inflection VC here, describing how their deep tech venture firm pairs human intuition and judgment with cutting-edge AI and machine learning technologies to identify and support innovators
“A Scalable and Adaptive System to Infer the Industry Sectors of Companies: Prompt + Model Tuning of Generative Language Models” paper by Lele Cao and his team at EQT here, introducing a sector inference system for thematic funds to pick up industry trends and promising companies
“CompanyKG: A Large-Scale Heterogeneous Graph for Company Similarity Quantification” paper by Lele Cao and his team at EQT here, publishing and benchmarking a knowledge graph that represents and learns diverse company features and relations
“Data-led investment: two fundamentally different approaches” by Olivier Huez from Red River West here, exploring the trade-off between “AI first” and “KPI first” approaches on a VC firm’s journey to becoming more data-driven
“GPT-4 Outperforms Humans in Pitch Deck Effectiveness Among Investors and Business Owners” by Clarify Capital here, finding that human investors prefer pitch decks created by algorithms over those crafted by humans
“Harnessing AI for Venture Capital: Identifying High-Growth Startups” by Any Uak Media here, providing an excellent overview of why investors need to become more data-driven
“Leveraging Data in Impact Investing: A Comparison with Data-Driven VC Processes” by Mustafa Torun from Invest-NL here, distinguishing data-driven investing for traditional VC firms and impact investors
“Using Deep Learning to Find the Next Unicorn: A Practical Synthesis on Optimization Target, Feature Selection, Data Split and Evaluation Strategy” paper by Lele Cao and his team at EQT here, sharing an in-depth literature review and synthesis on Deep Learning based approaches for investment screening
JOBS (Reach out to share relevant jobs here)
Analytics Engineer @EQT in Stockholm here
ML master student @EQT in Stockholm here
Data Engineering @Ethereal Ventures remote here
Senior Engineer @Inflection VC remote here
Data Scientist @Level VC in NY or Miami here
Data Engineering Lead @Techstars hybrid in Bolder, Colorado US, here
Senior Software Engineer at a leading growth equity firm in Menlo Park or New York here
“Data-driven VC Landscape 2023” report explores how leading investors leverage data & AI by shedding light on 151 top VCs, 65 thought leaders, 400+ tools, hands-on guides for integrating ChatGPT, LLMs, and a lot more
Most Awesome Founders podcast on “Leveraging data to build an augmented venture capital approach” with me here
Starwatcher Podcast #3 with Ernests Stals interviewing Pietro Casella here on how EQT leverages data and AI
“AI-powered VC Sheet” on ProductHunt by Vlastimil Vodizcka here to semantically search 50k investors by focus area
Key insights post from the “AI in Venture Capital” panel at Katapult Festival by Ties Boukema from Dawn Capital here
THIS MONTH’S DATA-DRIVEN VC EPISODES
Did I miss anything? Please reach out and let me know.
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If you have any suggestions, want me to feature an article, research, your tech stack or list a job, hit me up! I would love to include it in my next edition😎.