#69 Creating Cultural Transformations Using Data Science Leaders with Bülent Kiziltan – Head of Data Science & Analytics and Chief Data Scientist

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Dr. Bülent Kiziltan is an AI executive and an accomplished scientist who uses artificial intelligence to create value in many business verticals and tackles diverse problems in disciplines ranging from the financial industry, healthcare, astrophysics, operations research, marketing, biology, engineering, hardware design, digital platforms, to art. He has worked at Harvard, NASA, and MIT in close collaboration with pioneers of their respective fields. In the past 15+ years, he has led data-driven efforts in R&D and built multifaceted strategies for the industry. He has been a data science leader at Harvard and the Head of Deep Learning at Aetna leading and mentoring more than 200 scientists. 

In this episode, Bülent opens up the show discussing his background at places like Harvard, MIT, and NASA. Then, he explains his transition from astrophysics to business. He was intimately aware of the basic processes and procedures you use to extract information from data. The culture change was the biggest challenge of the transition. Business people are hesitant to work with people who are primarily familiar with academia. They tend to want a business veteran who has been in the business industry for ten or fifteen years. Bülent sees job descriptions which have a requirement of fifteen years of experience in data science, he believes this does not exist. People who have expertise in data science, they should have an academic background. 

Data leaders want to drive decisions and have informative interactions with your team members. If you a hard time understanding the ins and outs of different models, it will create an environment that does not make the technical team very happy. From a retention perspective, it will create a challenge for the company. Retention is a significant cost for the organization, having a meaningful conversation with leaders is one way to improve retention. If you approach data science in a limited fashion, you will go after the low hanging fruit and will miss on building internal strategies. Later, Bülent gives recommendations for implementing a culture in the workplace, explains how a leader should balance priorities, and the nuances of hierarchy in the startup space.


Enjoy the show!


We speak about:

  • [02:00] Bülent’s background

  • [05:50] The transition from astrophysics to business 

  • [08:45] Data leaders need technical experience 

  • [12:45] Academics still need soft skills 

  • [19:20] What data science can offer organizations 

  • [23:50] Addressing causal inferences

  • [25:30] Recommendations for implementing culture in the workplace 

  • [30:00] How a leader should balance priorities  

  • [36:10] Challenges Bülent currently faces in the industry  

  • [38:15] Hierarchy in the startup space

  • [40:45] What Bülent loves about data science 

  • [42:45] Future data challenges   


Resources:

Bülent’s Website: http://www.kiziltan.org/

Bülent’s LinkedIn: https://www.linkedin.com/in/bulentkiziltan/

Quotes:

  • “Culturally, I was surprised by the mindset of business leaders.”

  • “We asked individual members of the data science group to come up with their own ideas that can be implemented in the day-to-day business operations.”

  • “A diverse team is critically important for the business.”

  • “All companies will become AI companies in one way or another.”


Bülent Kiziltan is based in Cambridge, Massachusetts.


And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!





#65 Using the Love@Work Method to Improve Workplace Culture with Olivia Parr-Rud – Speaker, Award-Winning Author, and Data Scientist

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Olivia is an internationally known thought-leader, speaker, best-selling and award-winning author, and a data scientist who focuses on the interplay between technology, corporate leadership, and personal growth and happiness.  Throughout her career, she has blended analytic tools and holistic organizational practices to deliver successful solutions for her clients. As a lifelong spiritual seeker, Olivia began to see patterns that revealed the importance of love as a driver of business success.

In this episode, Olivia explains why she changed her major to statistics in grad school. Once she completed her degree, she joined a bank in San Francisco. Olivia built a model using logistic regression for the bank. It saved the company 17 million dollars a year in mail expense, making her an instant hero. Her desktop computer had a 500-megabyte hard drive when she was running SAS she couldn’t get into any other programs. Financial services had a vibrant climate for modelling because the behavioral data was so reliable. Behavioral data is so powerful because if a person has done something before, they are more likely to do it again.

Then, Olivia gives tips for explaining data science to non-technical people. Listen to what their goals and concerns are; then, speak and show the results that address their concerns. Data visualizations help because they are bright and easy to absorb. After her first publication, Data Mining Cookbook, Oliva started traveling and speaking at conferences. Her first book was a complete brain dump, whereas her second book, Business Intelligence Success Factors, was a lot of research. It was designed to take someone with a critical-thinking mind, and give them an argument for treating people well. 

Later, Olivia discusses Holacracy and why she believes this is a good model for where businesses will go in the future. Companies have to be much more agile. Holacracy allows knowledge and wisdom to come from everyone. In the future, companies will need to be able to turn on a dime to adapt and stay competitive. Holacracy is an agile idea that allows for companies to change how they operate immediately. Also, using Holacracy, people are allowed to create teams and are not necessarily solely autonomous. Stay tuned to hear Oliva and Felipe discuss the human side of data, the Love@Work Method, and using LEAP to improve workplace culture. 

Enjoy the show!

We speak about:

  • [01:40] How Olivia started in the data space  

  • [07:50] Data in the financial services industry 

  • [08:50] Oliva’s career history  

  • [13:35] Starting a consulting business 

  • [17:10] Tips for explaining data science to non-technical people

  • [18:30] Becoming a published author 

  • [24:45] Learning about Holacracy  

  • [29:00] Balancing Holacracy and teamwork 

  • [31:40] Combing data and human skills 

  • [40:20] The Love@Work Method

  • [47:15] One of Oliva’s professional fails   

  • [51:10] Using LEAP (love, energy, audacity, and proof)

  • [54:30] Following our intuitions 

Resources:

Oliva’s Website: www.lovemakeityourbusiness.com

Data Science Consulting: www.oliviagroup.com

 My Big ‘Why’ - https://tinyurl.com/LOVENEWCOMPETITIVEEDGE

LOVE@WORK now available at https://tinyurl.com/OLIVIAPRLOVEATWORK - A Silver Nautilus Book Award-Winner 

The LOVE@WORK MethodTM now available at https://tinyurl.com/TheLOVE-WORKMethod

What is your Corporate Love Quotient? Find out here www.corporatelovequotient.com   

Love@Work Method to Improve Workplace Culture with Olivia Parr-Rud

Oliva’s Social Media:

Facebook: https://www.facebook.com/LoveMakeItYourBusiness/

LinkedIn: https://www.linkedin.com/in/oliviagroup/

Twitter handle: #OliviaParrRud  

YouTube: www.OliviaOnYouTube.com

Instagram: Love.MakeItYourBusiness

Quotes:

  • “Companies need to be able to adapt much more quickly now.”

  • “As more things get automated, the need for human factors are much more prominent.”

  • “Each manager should speak to their direct reports at least once a day.”

  • “People who have better experiences at work go home happier.”


Thank you to our sponsors:

UNSW Master of Data Science Online: studyonline.unsw.edu.au

Datasource Services: datasourceservices.com.au or email Will Howard on will@datasourceservices.com.au

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Olivia Parr-Rud is based in Los Angeles, California.

And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show!