S2E2 - What Crypto Data Teams Do Differently with Emily Loh
What Crypto Data Teams Do Differently with Emily Loh
Episode Snapshot
In this illuminating conversation, Emily Loh reveals how leading a data team in the volatile crypto space has forced innovations in resource allocation, strategic prioritisation, and AI implementation that data leaders across all industries can apply for greater impact.
Guest Introduction
Emily Loh serves as Director of Data at MoonPay, where she leads a 15-person team spanning data engineering, data science, and machine learning in a fast-evolving crypto environment. With previous experience at Coinbase and a surprising background in literature rather than computer science, Emily brings a unique storytelling perspective to data leadership that emphasises business outcomes over technical outputs.
Conversation Highlights
The discussion takes an unexpected turn when Emily reveals her humanities background, noting that her literature studies prepared her surprisingly well for data leadership: "I never thought I'd be in data, but specifically I studied literature. And in my career right now, I'm just like, 'oh, this is just really just storytelling.'" This insight evolves into a thoughtful exchange about how effective data work requires understanding human needs first, with technical implementation second.
A particularly candid moment occurs when Emily confesses, "Full disclosure, I am a formed people pleaser," sparking an authentic discussion about the struggle many data leaders face in saying "no" to low-value requests. Aaron and Emily explore how this seemingly simple act requires both courage and strategic frameworks to implement effectively.
Actionable Insights
1. Implement the 20/40/40 resource allocation framework - Emily's team divides their time into 20% BAU (business as usual), 40% building, and 40% research, creating space for innovation even during challenging market periods. Practical Application: Start by auditing your team's current time allocation, then gradually shift toward this balanced model using clear opportunity sizing frameworks to evaluate potential projects.
2.Break free from the "service trap" by transforming request handling - Instead of immediately building requested dashboards, train your team to ask "What decisions are you trying to make?" to focus on outcomes rather than outputs. Practical Application: Develop a structured intake process that guides stakeholders toward better request formulation and establishes clear value criteria for accepting work.
3. Use AI strategically to eliminate team drudgery - At MoonPay, tools like Cursor help automate tedious tasks such as YAML file management, freeing analyst time for strategic work. Practical Application: Survey team members about their most tedious regular activities, then select appropriate AI tools that can automate these specific tasks while measuring success through time savings.
4. Design data systems for uncertain futures - In crypto's rapidly changing landscape, Emily's team builds flexible architectures that can adapt to regulatory shifts and market changes. Practical Application: Implement modular data models that can evolve without complete rebuilds while maintaining strong data quality foundations that support agility regardless of specific technologies.
Industry Context
This conversation arrives at a critical inflection point for data leaders across industries, as generative AI promises transformation while many teams still struggle with the fundamental challenge of delivering strategic value rather than reactive reporting. Emily's experience navigating crypto's extreme volatility provides a stress-tested framework applicable to any data team facing resource constraints and rapid change.
Why Listen
This episode is essential for mid to senior-level data leaders who feel trapped in reactive work cycles and are seeking practical frameworks to increase their strategic impact. Whether you're in a traditional enterprise struggling with legacy approaches or a high-growth startup trying to balance immediate demands with future needs, Emily's battle-tested insights provide immediately applicable strategies for transformation.
Episode Details
Length: 37 minutes
Release Date: March 2025
Episode Number: #127
This conversation with Emily Loh offers rare insight into how crypto's extreme conditions have forced innovation in data team management—innovations that can give any data leader a competitive advantage in today's rapidly evolving landscape.
Episode Snapshot
In this illuminating conversation, Emily Loh reveals how leading a data team in the volatile crypto space has forced innovations in resource allocation, strategic prioritisation, and AI implementation that data leaders across all industries can apply for greater impact.
Guest Introduction
Emily Loh serves as Director of Data at MoonPay, where she leads a 15-person team spanning data engineering, data science, and machine learning in a fast-evolving crypto environment. With previous experience at Coinbase and a surprising background in literature rather than computer science, Emily brings a unique storytelling perspective to data leadership that emphasises business outcomes over technical outputs.
Conversation Highlights
The discussion takes an unexpected turn when Emily reveals her humanities background, noting that her literature studies prepared her surprisingly well for data leadership: "I never thought I'd be in data, but specifically I studied literature. And in my career right now, I'm just like, 'oh, this is just really just storytelling.'" This insight evolves into a thoughtful exchange about how effective data work requires understanding human needs first, with technical implementation second.
A particularly candid moment occurs when Emily confesses, "Full disclosure, I am a formed people pleaser," sparking an authentic discussion about the struggle many data leaders face in saying "no" to low-value requests. Aaron and Emily explore how this seemingly simple act requires both courage and strategic frameworks to implement effectively.
Actionable Insights
1. Implement the 20/40/40 resource allocation framework - Emily's team divides their time into 20% BAU (business as usual), 40% building, and 40% research, creating space for innovation even during challenging market periods. Practical Application: Start by auditing your team's current time allocation, then gradually shift toward this balanced model using clear opportunity sizing frameworks to evaluate potential projects.
2.Break free from the "service trap" by transforming request handling - Instead of immediately building requested dashboards, train your team to ask "What decisions are you trying to make?" to focus on outcomes rather than outputs. Practical Application: Develop a structured intake process that guides stakeholders toward better request formulation and establishes clear value criteria for accepting work.
3. Use AI strategically to eliminate team drudgery - At MoonPay, tools like Cursor help automate tedious tasks such as YAML file management, freeing analyst time for strategic work. Practical Application: Survey team members about their most tedious regular activities, then select appropriate AI tools that can automate these specific tasks while measuring success through time savings.
4. Design data systems for uncertain futures - In crypto's rapidly changing landscape, Emily's team builds flexible architectures that can adapt to regulatory shifts and market changes. Practical Application: Implement modular data models that can evolve without complete rebuilds while maintaining strong data quality foundations that support agility regardless of specific technologies.
Industry Context
This conversation arrives at a critical inflection point for data leaders across industries, as generative AI promises transformation while many teams still struggle with the fundamental challenge of delivering strategic value rather than reactive reporting. Emily's experience navigating crypto's extreme volatility provides a stress-tested framework applicable to any data team facing resource constraints and rapid change.
Why Listen
This episode is essential for mid to senior-level data leaders who feel trapped in reactive work cycles and are seeking practical frameworks to increase their strategic impact. Whether you're in a traditional enterprise struggling with legacy approaches or a high-growth startup trying to balance immediate demands with future needs, Emily's battle-tested insights provide immediately applicable strategies for transformation.
Episode Details
Length: 37 minutes
Release Date: March 2025
Episode Number: #127
This conversation with Emily Loh offers rare insight into how crypto's extreme conditions have forced innovation in data team management—innovations that can give any data leader a competitive advantage in today's rapidly evolving landscape.