The Alternative Data Podcast Mark Fleming-Williams

In this episode I speak to Don D’Amico, formerly of Neudata and now the CEO and Founder of Glacier Network, a new company that helps data buyers manage the legal considerations in their data chain.
In our conversation we track the evolving alternative data regulation conversation, and talk about the kinds of pitfalls that can blow up a data provider or hurt a buyer that has not written their contracts with enough care.
Separately, I am in Singapore for Battlefin next week so if you are in that direction and want to talk about an interesting dataset, do get in touch.
DISCLAIMER
This podcast is an edited recording of an interview with Don D’Amico recorded in March 2024. The views and opinions expressed in this interview are those of Don D’Amico and Mark Fleming-Williams and do not necessarily reflect the official policy or position of either CFM or any of its affiliates. The information provided herein is general information only and does not constitute investment or other advice. Any statements regarding market events, future events or other similar statements constitute only subjective views, are based upon expectations or beliefs, involve inherent risks and uncertainties and should therefore not be relied on. Future evidence and actual results could differ materially from those set forth, contemplated by or underlying these statements. In light of these risks and uncertainties, there can be no assurance that these statements are or will prove to be accurate or complete in any way.


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In this episode I speak to Ken Book, the CEO and Founder of Fluid Markets, a new company that is trying to make KPIs tradeable by investors.
In our conversation we walk through Ken’s founder story, from a summer at Goldman Sachs through Y Combinator on the path to realising his vision, which when achieved will make the relationship between alternative data and the markets a great deal tighter.
If you know of an alternative data story that needs to be heard on this podcast, please do get in touch.
DISCLAIMER
This podcast is an edited recording of an interview with Kenneth Book recorded in February 2024. The views and opinions expressed in this interview are those of Kenneth Book and Mark Fleming-Williams and do not necessarily reflect the official policy or position of either CFM or any of its affiliates. The information provided herein is general information only and does not constitute investment or other advice. Any statements regarding market events, future events or other similar statements constitute only subjective views, are based upon expectations or beliefs, involve inherent risks and uncertainties and should therefore not be relied on. Future evidence and actual results could differ materially from those set forth, contemplated by or underlying these statements. In light of these risks and uncertainties, there can be no assurance that these statements are or will prove to be accurate or complete in any way.


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In this episode I speak to Matt Ober, a godfather in Data Sourcing, to discuss his history finding data in the early days of the space and his new project – Initial Data Offering.
If you know of an alternative data story that needs to be heard on this podcast, please do get in touch.
DISCLAIMER
This podcast is an edited recording of an interview with Matt Ober recorded in January 2024. The views and opinions expressed in this interview are those of Matt Ober and Mark Fleming-Williams and do not necessarily reflect the official policy or position of either CFM or any of its affiliates. The information provided herein is general information only and does not constitute investment or other advice. Any statements regarding market events, future events or other similar statements constitute only subjective views, are based upon expectations or beliefs, involve inherent risks and uncertainties and should therefore not be relied on. Future evidence and actual results could differ materially from those set forth, contemplated by or underlying these statements. In light of these risks and uncertainties, there can be no assurance that these statements are or will prove to be accurate or complete in any way.

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In this episode I invite back Ed Lavery, to discuss his new role at Placer.AI, the US location data provider, following his previous appearance on the Similarweb episode.
In our conversation, Ed and I discuss the strengths of location data, alternative data’s development and what he plans to bring with him from his previous role.
Separately, I will be hosting the macro panel at Battlefin in London tomorrow, so come and say hi if you’re there.
DISCLAIMER
This podcast is an edited recording of an interview with Ed Lavery recorded in September 2023. The views and opinions expressed in this interview are those of Ed Lavery and Mark Fleming-Williams and do not necessarily reflect the official policy or position of either CFM or any of its affiliates. The information provided herein is general information only and does not constitute investment or other advice. Any statements regarding market events, future events or other similar statements constitute only subjective views, are based upon expectations or beliefs, involve inherent risks and uncertainties and should therefore not be relied on. Future evidence and actual results could differ materially from those set forth, contemplated by or underlying these statements. In light of these risks and uncertainties, there can be no assurance that these statements are or will prove to be accurate or complete in any way.

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Welcome to the Alternative Data Podcast, powered by CFM. I’m Mark Fleming-Williams.
In this episode I speak to Jason DeRise, who was one of the very earliest employees of UBS’s alternative data platform, Evidence Lab, and who has recently become a very active and followed commentator on the alternative data space.
In our conversation, Jason and I discuss the UBS Evidence Lab’s development, as well as Jason’s views on alternative data’s future consolidation, how banks approach the space, and the data he wishes he could have got his hands on.
DISCLAIMER
This podcast is an edited recording of an interview with Jason DeRise recorded in August 2023. The views and opinions expressed in this interview are those of Jason DeRise and Mark Fleming-Williams and do not necessarily reflect the official policy or position of either CFM or any of its affiliates. The information provided herein is general information only and does not constitute investment or other advice. Any statements regarding market events, future events or other similar statements constitute only subjective views, are based upon expectations or beliefs, involve inherent risks and uncertainties and should therefore not be relied on. Future evidence and actual results could differ materially from those set forth, contemplated by or underlying these statements. In light of these risks and uncertainties, there can be no assurance that these statements are or will prove to be accurate or complete in any way.

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In this episode I speak to Mark Ainsworth, the former head of Data Science at Schroders, a two-and-a-half-centuries-old asset manager that is notable for its use of alternative data.
In this episode, Mark and I discuss what made Schroders take this unusual route, and how his work there differed from the more familiar alternative data working patterns of hedge funds.
We also touch on a subject dear to Mark’s heart, which is neurodiversity and its higher propensity amongst technologists.
DISCLAIMER
This podcast is an edited recording of an interview with Mark Ainsworth recorded in June 2023. The views and opinions expressed in this interview are those of Mark Ainsworth and Mark Fleming-Williams and do not necessarily reflect the official policy or position of either CFM or any of its affiliates. The information provided herein is general information only and does not constitute investment or other advice. Any statements regarding market events, future events or other similar statements constitute only subjective views, are based upon expectations or beliefs, involve inherent risks and uncertainties and should therefore not be relied on. Future evidence and actual results could differ materially from those set forth, contemplated by or underlying these statements. In light of these risks and uncertainties, there can be no assurance that these statements are or will prove to be accurate or complete in any way.

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