Chief Executive Officer & Director, Artisan Partners Asset Mgmt
Search every verified Eric Colson interview, podcast appearance, and on-the-record quote — each transcript cross-checked by AI and human review to confirm speaker identity. Eric Colson, CEO of Artisan Partners and a former data science executive at Netflix and Stitch Fix, has discussed the challenges companies face in leveraging data science effectively. In a February 2025 podcast, Colson argued that many firms treat data scientists as a support function, limiting their impact by only executing ideas from business teams. He advocated for giving data scientists autonomy and accountability for measurable outcomes, and for using trial-and-error experimentation with cheap failures to find winshol. Colson also emphasized the importance of decoupling algorithms from applications and enabling data scientists to frame problems rather than simply optimize within inherited constraints. In earlier appearances, Colson addressed the asset management industry, stating that "a lot of true active management got diluted" as firms prioritized growth over differentiation. He described Artisan's model as centered on investments, people, and trust, and noted the firm's introduction of "investment degrees of freedom" to allow teams to deviate from benchmarks. Colson also discussed value investing, saying Artisan seeks stocks that are out of favor and positions itself differently from the herd, and highlighted the firm's expansion into global and alternative strategies, including a China post-venture strategy.
“The main challenge is that there's a lot of companies that treat their data scientists as a support function — their role is to help the various business teams — and when that happens the ideas come only from the business teams and you leave a lot on the table because many ideas can only come the other way, from data s...”
“You need to establish a bidirectional flow of ideas — if data science is merely handed down requirements and just asked to execute, that will limit how data scientists contribute.”
“We reframed the recommendation problem at Stitch Fix as logistic regression and scaled scores between zero and one to represent purchase probability — that made the scores interpretable, learnable from data, and far easier to extend and scale than the ad‑hoc rules we had before.”
“Data scientists are uniquely valuable because they bring two things the rest of the company often doesn't have: a different cognitive repertoire (ways of framing problems and algorithmic patterns) and different information from being deeply immersed in the data.”
“I advocate trial and error: instead of trying just a few ideas and overplanning, try many ideas and make failures as cheap as possible — volume will find the wins, and the wins can outweigh the losses.”
“Before you roll out an idea to all customers you should try it first as an experiment — allocate a random sample, run an A/B test, and get causal evidence before wide deployment.”
“Algorithms are often cheap to explore and try: the data is at your fingertips, you can get quick exploratory signal from historical data, and with the right infrastructure you can run low-cost trials in production.”
“Optionality matters: algorithmic experiments are usually easy to pull back (feature flags, limited samples) so failures are contained while wins can be rolled out and amplified — that asymmetry justifies running many experiments.”
“Decouple algorithms from the applications that house them: let engineering own the app and the algorithms team own the decision logic (served via APIs) so algorithms can iterate autonomously without constantly burdening engineering.”
“If you give data scientists autonomy to try ideas, you should also saddle them with accountability for impact — make them responsible for measurable business outcomes like revenue or retention.”
“The asset management industry is highly competitive with low barriers to entry, and for companies to withstand the test of time, you have to know who you are—being in the business of investments first, people second, and trust third.”
“A lot of true active management got diluted over time as firms tried to grow at an abnormal rate, leading to product proliferation and product engineering that now is deemed exposure management rather than pure active management.”
“Active management is a highly differentiated strategy that brings philosophy, opinion, and judgment into a portfolio to outperform the index, as opposed to just giving exposure, and we're seeing a return to that approach.”
“Asset management is the one industry where you get penalized for changing your philosophy, even if you realize there's a better way to do things, which makes balancing consistency and innovation a real challenge.”
“At Artisan, we introduced 'investment degrees of freedom' allowing investment teams to leverage the current environment and be different from the index, which clients have come to expect and accept over the last five to seven years.”
Eric Colson—former Chief Algorithms Officer at Stitch Fix and VP of Data Science and Machine Learning at Netflix—explains why ...
Citywire South Africa Editor, Patrick Cairns, speaks to the CEO of Artisan Partners, Eric Colson. He reflects on the lessons that the ...
The case for value is not just about finding high-quality companies at discounted prices; it's also about avoiding the herding, ...
Most companies data science caps out I'd say a director level but by providing these executive level rules you can enable a full ...
Eric Colson, CEO, at the Artisan Partners Investment Forum, shares how high value-added investments, a talent driven business ...
The ART program provides a unique view of our firm with three distinct rotations across different business teams and locations, ...
Subscribe to O'Reilly on YouTube: http://goo.gl/n3QSYi Follow O'Reilly on: Twitter: http://twitter.com/oreillymedia Facebook: ...
ai.bythebay.io Nov 2025, Oakland, full-stack AI conference Scale By the Bay 2019 is held on November 13-15 in sunny Oakland, ...
Sign in to search the full transcript archive, filter by topic, and access every quote from Eric Colson.
The summary and quote tags on this profile are produced with AI assistance from verified, first-person interview transcripts, then checked by our team to confirm the speaker's identity and the accuracy of every quote. See how we verify →