5 Critical Roles That Every Data Science Team Must Hire🧍
5 Critical Roles That Every Data Science Team Must Hire🧍
Hello,
A new milestone - this is our 50th Newsletter 🎊 ! Thanks for your feedback and support all along.
This edition rounds up some AI predictions for 2023.. and their legal implications. Understandably, ChatGPT, Dall E, Stable Diffusion et al feature prominently.
This newsletter will take you about 4 minutes to read.
I. Spotlight: 5 Critical Roles That Every Data Science Team Must Hire🧍
Building a data science product is quite like constructing your home. Using this analogy let’s look at the five roles and skills that the best data science teams hire for.
The CEO of a large financial services firm was a big supporter of advanced analytics. He decided to get his organization started on the path toward data science.
How did the organization plan this journey? By recruiting data scientists, of course! They hired 1000 data scientists, each at an average cost of $250,000 a year. Data scientists are hard to come by, so the CEO was very proud of this achievement.
Several months and millions of dollars later, the business benefits were not there. And upon further investigation, the organization found that these ‘experts’ were not data scientists at all!
McKinsey reports that neither this firm’s CEO nor the human resources group understood the data scientist role. They naively assumed that a bunch of high-priced technical experts could transform the organization into a data-driven one on their own.
Data scientists often come with excellent machine learning skills, but they stumble at choosing the right business problems to solve. They struggle to scale the algorithms in production. And, they fail terribly in translating the data insights into a format that business users can consume.
Data science is a team sport. Every team must hire five roles if they are serious about data-driven decision-making.
Building successful data science teams
Creating a data science solution is not very different from building your home.
II. Industry Roundup:
1. Article: 7 AI predictions for 2023 from IT leaders
06 minutes | The Enterprisers Project | Katie Sanders
What’s trending in the age of AI? Here are seven predictions on AI from technology leaders. The potential impacts of the technology are wide-ranging—as are the related forecasts, on everything from sentient to generative and responsible AI, to collaboration and automation. Which of these excites you the most?
2. Article: Where will AI go next?
05 minutes | MIT Technology Review | Melissa Heikkilä
ChatGPT and other AI generators from top tech labs occupied the headlines in 2022. What about 2023? Hear from top executives at some of the world’s biggest AI labs on what will drive the conversation next year. Expect some big breakthroughs in multimodal AI models apart from continuing advances in generative AI. The article dives into the AI angle of the Twitter fiasco as well.
3. Article: ‘Legal minefield’: The risk of commercializing AI-generated images
06 minutes | Silicon Republic | Leigh Mc Gowran
With the increasing popularity of text-to-image tools like DALL-E, legal concerns rise. To use such tools in a business setting, it is important to ensure that the data used to train AI models is obtained legally and doesn’t infringe on any rights. Ditto for text/code/video/content generators. The legal impact is very high and this could land enterprises in trouble. Should we expect some high-profile lawsuits in 2023?
III. From my Desk:
1. Article: 5 data science articles IT leaders should read now
1 min | Enterprisers Project
The Enterprisers Project has released the readers' Top-5 favorite articles on data science from 2022. Glad to see my article in this list - ‘Low-code data science platforms: 3 things IT leaders should know’. Check out all the articles.
2. Video: Protecting African Elephants with Deep Learning
4 min | YouTube
In this video, I explain how AI was used to protect African elephants from poachers. With the help of advanced machine learning algorithms, it’s possible to accurately detect, identify, and count various species in their natural habitats. Watch the video to know more about this exciting AI application for wildlife conservation.
We have all heard of autonomous cars, how about autonomous bikes?!
Thank you for subscribing and reading the newsletter. I appreciate your attention,
Ganes.
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My Website | LinkedIn | Twitter | YouTube
I’m Ganes Kesari. I publish ‘Data-Driven Future’ to help understand how data shapes our world, explore key trends, and explain what they mean for you today. I speak and write to demystify data science for decision-makers and organizations.
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