In this episode of Data Analytics Chat, we welcome Misha Trubskyy, head of Claims Data Science at Mercury Insurance. Misha shares his journey from academia to corporate life, highlighting his transition from econometrics to leading data science initiatives in insurance. He discusses the significance of continuous learning, the challenges of AI and data implementation, and the importance of hiring and retaining top talent. Misha also delves into his leadership principles, the value of technical proficiency, and the importance of empathy in managing teams. Key issues such as the evolving hiring landscape, market conditions, and strategies for organizational growth are explored in-depth.

00:00 Introduction and Personal Philosophy
00:14 The Importance of Continuous Learning
00:44 Challenges in the AI and Data Science Field
01:20 Guest Introduction: Misha Ky
02:24 Misha's Career Journey
03:43 Current Excitements in AI and Data Science
06:09 Navigating Human Elements in Claims
07:37 Leadership Challenges and Lessons
11:28 The Value of Individuality in Leadership
19:31 Advice for Aspiring Data Leaders
29:52 Hiring Challenges in AI and Data Science
37:02 Finding the Right People for the Job
37:23 The Importance of Critical Thinking
37:41 Authenticity in Interviews
38:26 The Role of Technology in Interviews
38:51 Evaluating Candidates Beyond Technical Skills
41:36 The Misconception About Technical Skills
42:25 Personality and Attitude in Hiring
44:21 Challenges in the Job Market
48:55 Investing in Junior Staff
01:04:33 Retention Strategies for Top Performers
01:10:03 Future of the Hiring Landscape
01:13:42 Conclusion and Final Thoughts

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In this episode of Data Analytics Chat, we welcome Carol Kim, Executive Director at IBM, who shares her intriguing journey from a finance background to leading technology, data, and AI at IBM's Global Real Estate Organization. Carol talks about her career transformation, the importance of curiosity, authentic leadership, and the role of storytelling in decision-making. The episode also delves into the significance of data governance and quality for data-driven decision-making and how to build effective data governance frameworks. Carol further discusses adapting to different cultures, continuous reinvention, and the hidden costs of poor data quality. Tune in to get insights into navigating a tech-driven career and the pivotal role of data in modern enterprises.

00:00 Introduction: The Power of Willingness to Learn
01:12 Welcome to Data Analytics Chat
02:01 Carol Kim's Career Journey
02:57 The Role of Data in Real Estate
03:38 Adapting to Different Cultures
07:54 The Importance of Storytelling in Data
09:59 Challenges in Leadership and Career Transitions
15:13 The Significance of Data Governance and Quality
24:06 Conclusion and Final Thoughts

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In this episode of Data Analytics Chat, host Ben welcomes Ilya Meizin, SVP Head of AI Solutions at Dun & Bradstreet. Ilya shares his career journey from management consulting to leading AI solutions, highlighting the importance of implementation, continuous learning, and cross-domain expertise. He discusses the evolution of AI agents, their capabilities, and the shift from linear models to stateful, autonomous agents. The conversation delves into complexities of scaling AI, embedding agents in enterprise architecture, and balancing technical innovation with business value. Ilya also emphasizes the necessity of high-quality data and the role of collaboration across departments for successful AI deployment.

00:00 Introduction and Initial Insights
01:14 Guest Introduction and Career Overview
02:45 Transition from Strategy to Implementation
04:15 Learning and Adapting in Consulting
05:35 Defining Career Moments
10:35 Handling Challenges and Stress
13:03 Leadership and Team Dynamics
14:45 Balancing Technical and Business Skills
20:01 Focus and Credibility in Leadership
23:18 Introduction to AI Agents
23:39 Capabilities of AI Agents
24:22 Technical Aspects of AI Agents
25:39 Complex Problem Solving with AI Agents
28:40 High-Value Use Cases for AI Agents
32:14 Team Collaboration in AI Deployment
33:19 Challenges in Scaling AI Agents
37:21 Data Quality and AI Agents
45:12 Future of AI Agents in Enterprises
48:17 Conclusion and Final Thoughts

Thank you for listening!