#86 [DataFramed Careers Series #1] Launching a Data Career in 2022 (with Sadie St. Lawrence)
Skills:
Data Literacy60%
Today is the start of a four-day careers series covering breaking into data science in 2022. With so so much demand for data jobs today, we wanted to demystify the ins and outs of accelerating a career in data. In this series, we will interview a diverse range of thought leaders and experts on the different aspects of standing out from the crowd in the job hunt.
Our first guest in the DataFramed Careers Series is Sadie St. Lawrence. Sadie St Lawrence is the Founder and CEO of Women in Data, the #1 Community for Women in AI and Tech. Women in Data is a community of over 20,000 individuals and has representation in 17 countries and 50 cities. She has trained over 350,000 people in data science and is the course developer for the Machine Learning Certification for UC Davis. In addition, she serves on multiple start-up boards, and is the host of the Data Bytes podcast.
Sadie joins the show to talk about her career journey in data science and shares the best lessons she has learned in launching data careers.
Throughout the episode, we discuss:
- The different types of data career paths available
- How to break into your data science career
- How to build strong mentor/mentee relationships
- Best practices to stand out in a competitive industry
- Building a strong resume and standing out from the crowd
Please subscribe to the podcast on Itunes and give us a rating and review!
Itunes Link: https://podcasts.apple.com/us/podcast/dataframed-careers-series-1-launching-a-data-career-in-2022/id1336150688?i=1000564490436
This is the DataCamp podcast link, check it out for the show notes and other goodies: https://www.datacamp.com/podcast/dataframed-careers-series-1-launching-a-data-career-in-2022
Some interesting reads:
New Hire Spotlight: Creating the Best Platform to Fight Data Illiteracy | DataCamp | DataCamp https://www.datacamp.com/blog/new-hire-spotlight-creating-the-best-platform-to-fight-data-illiteracy
Environment Variables For Data Scientists | DataCamp https://
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