
Sign up to save your podcasts
Or
Send us a text
Innovating on Wall Street: Kristen McGarry on Data, AI, and Technical Sales
๐ง Tune in for an insiderโs look at the technical strategies shaping the future of finance.
Kristen McGarry, Principal Account Technical Lead for IBMโs Financial Services Market, returns to Making Data Simple to dive deeper into the intersection of technology and Wall Street. Based in NYC, Kristen works with the worldโs largest financial institutions to drive innovation, accelerate time to value, and implement cutting-edge solutions across software, hardware, and services.
In this episode, we break down the realities of technical sales, the evolving role of data science in finance, and what Wall Street is getting right (or wrong) about AI. Kristen also shares key insights on the challenges of working with financial giants and predictions for the future of tech in banking.
โฑ Episode Highlights:
๐ 02:57 โ An Intro to Kristen McGarry
๐ 04:36 โ Why IBM?
๐ 09:25 โ The Attraction of Data Science
๐ 11:51 โ A Day in the Life of an Account Technical Leader
๐ 13:30 โ Technical Sales versus Sales
๐ 15:05 โ Continuing to Innovate
๐ 19:09 โ Dealing with Wall Street
๐ 20:17 โ The Methodology
๐ 22:23 โ The How of Technical Sales
๐ 23:05 โ Continuous Learning
๐ 28:03 โ Management System
๐ 30:34 โ Wall Street Learnings
๐ 32:20 โ Biggest Challenge
๐ 33:08 โ The Data Challenge
๐ 34:22 โ Best Data Science Use Cases in Finance
๐ 36:14 โ What Do Clients Miss on AI?
๐ 38:09 โ Predictions
LinkedIn: https://www.linkedin.com/in/kristen-mcgarry/
Website: https://www.ibm.com/
#MakingDataSimple #DataScience #AIinFinance #TechSales #WallStreet #IBM #Innovation #FinancialServices #Leadership #ContinuousLearning #AI
Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.
4.9
88 ratings
Send us a text
Innovating on Wall Street: Kristen McGarry on Data, AI, and Technical Sales
๐ง Tune in for an insiderโs look at the technical strategies shaping the future of finance.
Kristen McGarry, Principal Account Technical Lead for IBMโs Financial Services Market, returns to Making Data Simple to dive deeper into the intersection of technology and Wall Street. Based in NYC, Kristen works with the worldโs largest financial institutions to drive innovation, accelerate time to value, and implement cutting-edge solutions across software, hardware, and services.
In this episode, we break down the realities of technical sales, the evolving role of data science in finance, and what Wall Street is getting right (or wrong) about AI. Kristen also shares key insights on the challenges of working with financial giants and predictions for the future of tech in banking.
โฑ Episode Highlights:
๐ 02:57 โ An Intro to Kristen McGarry
๐ 04:36 โ Why IBM?
๐ 09:25 โ The Attraction of Data Science
๐ 11:51 โ A Day in the Life of an Account Technical Leader
๐ 13:30 โ Technical Sales versus Sales
๐ 15:05 โ Continuing to Innovate
๐ 19:09 โ Dealing with Wall Street
๐ 20:17 โ The Methodology
๐ 22:23 โ The How of Technical Sales
๐ 23:05 โ Continuous Learning
๐ 28:03 โ Management System
๐ 30:34 โ Wall Street Learnings
๐ 32:20 โ Biggest Challenge
๐ 33:08 โ The Data Challenge
๐ 34:22 โ Best Data Science Use Cases in Finance
๐ 36:14 โ What Do Clients Miss on AI?
๐ 38:09 โ Predictions
LinkedIn: https://www.linkedin.com/in/kristen-mcgarry/
Website: https://www.ibm.com/
#MakingDataSimple #DataScience #AIinFinance #TechSales #WallStreet #IBM #Innovation #FinancialServices #Leadership #ContinuousLearning #AI
Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.
3,180 Listeners
1,021 Listeners
9,070 Listeners
1,872 Listeners
296 Listeners
111,154 Listeners
55,920 Listeners
3,981 Listeners
1,445 Listeners
266 Listeners
5,281 Listeners
1,537 Listeners
2 Listeners
450 Listeners
87 Listeners