Dan Costanza, Chief Data Scientist at Citi, joins me for the first episode in the new “Bitesize Insights for Data Driven Leaders” Series. Dan opens the show by explaining how he got interested in data. After graduating from college, Dan went into an investment banking role. Eventually, he received an exciting project that got him started down the data path. Dan says as someone who didn’t study computer science in school, it has been a heavy lift trying to get those technical skills up to par. During a code-heavy project, Dan needed to learn how to break up the project and work through it. Also, he learned how to think about sampling data without bias.
Then, Dan explains the importance of emotional intelligence for data science. Conscientiousness and emotional intelligence are the things that you can actually interview for. Instead of judging people on their grades, we need to judge people on their ethics, communication skills, and willingness to work in teams. In India, Dan set up a data science team. The talent in India is insane. However, there are cultural differences Dan needed to work through. For instance, he told his team that they needed to speak up when they had ideas. If you create space for people to bring their own thoughts, you’ll hear loads of good suggestions. Before Dan told his team that, they would withhold useful information.
Quotes:
“When you look at the hiring research again, like there are two real categories and the one is things you don’t interview for, which are the intellectual horsepower things and those are - how smart you are, do you have some specific skills I need. The word that always comes up on the other side is conscientiousness, and that encompasses the stuff we talked about at the beginning, and the emotional intelligence, teamwork parts of it and those are the things you do actually interview for. Which is counterintuitive for a lot of people who work in quanti type roles because you want to ask people really hard questions, to see if they are smart, but the problem is the data doesn’t support that as being predictive of anything when you control for their grades.”Read the full episode summary here: Episode #124
Enjoy the show!
#126 Data-Driven Approaches From Politics to Aerospace with Adam Bonnifield – VP Artificial Intelligence
#125 Transitioning From Academia to Business – The Skills Gap with David Hardoon – Senior Adviser for Data and Artificial Intelligence
#123 Why We Need to Focus on Implementing Data Governance with Michelle Pinheiro – Head of Enterprise Data Governance
#122 Optimising Conversational AI Dialogue Systems with Dr. Maria Aretoulaki - CEO
#121 The Strategic Importance of Data Warehousing and Analytical Software With Craig Rowlands – Senior Executive Information Management
#120 Natural Language Processing with Catherine Havasi – CEO
#119 Finding Success in Data-Driven Entrepreneurship with Dr. AnnMaria De Mars – President
#118 Smart Tech Meets a Smart Dr’s Passion to Solve Blindness with Andrew Bastawrous – Co-Founder & CEO
#117 Driving commercial opportunities at F1 with Max Métral – Senior Analytics Manager
#116 Navigating The COVID-19 Landscape: Changes For Data Scientists in the Job Market
#115 AI Ethics with Stephanie Kelley – PhD Candidate in AI Ethics at Queen's University, IEEE Ethically Aligned Design for Finance Working Committee Member
#114 Grokking Artificial Intelligence Algorithms with Rishal Hurbans – Solutions Architect
#113 Practices of the Python Pro with Dane Hillard – Author and Lead Web Application Developer
#112 How To Ensure Success In Your Work
#111 Machine Learning with TensorFlow with Chris Mattmann – Author / Manager, Chief Technology and Innovation Officer
#110 Explainable AI Methods for Structured Data
#109 Programming, Bioinformatics and the Future of Computer Programming with Ken Youens-Clark – Senior Scientific Programmer
#108 Should I Become More Technical or Business Focused in my Data Science Career?
#107 Developing New Products Using Machine Learning with Max Sklar - Engineering and Innovation Labs Advisor and Podcast Host
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