International Women’s Engineering Day

Today is International Women’s Engineering Day 2019, and with women making up just 16% of engineering professionals, it’s important to highlight amazing women in the field, and encourage more young women to consider a career in engineering, specifically data science and data engineering in the process.

The Data Science Diversity Gap: Where Are the Women?

In this contributed article, freelance human Avery Phillips believes that data science is a much more creative field than you think. Diversifying data science teams means opening the door to different, more creative perspectives. This is especially important when the tech that’s being developed will specifically combat women’s issues, such as women’s healthcare. Show your innovative side in order to be of true value to the company you work for. Modern, savvy companies won’t care about your gender if you’re brilliant at what you do.

Infographic: The Typical Data Scientist 2019

It’s hardly a surprise to anyone in the tech and related industries that “data scientist” is the best job to have these days. After all, this has been what sources like the Harvard Business Review and Glassdoor report for what is now four years in a row. And even if we take the base salary of $108,000 out of the equation, the position is still plenty attractive on all other dimensions. The infographic below, produced by our friends over at 365DataScience, suggests that the field is evolving and, with it, the typical professional evolves as well.

Data Scientist Is Still a Hot Job and Pays Well Too

“Data Scientist: The Sexiest Job of the 21st Century.” So proclaimed the Harvard Business Review in 2012. Six years later and the job of a data scientist has only grown sexier. More employers than ever are looking to hire data scientists. Yet while the supply of data science job seekers is growing, it’s far outstripped by the rising demand in postings, meaning there potentially may not be enough skilled applicants. So the bargaining power in data science remains with the job seekers, according to new research from Indeed.

The Time Has Come for Data Scientists’ Own GitHub

In this contributed article, email marketer and writer Adelina Benson discusses how data collaboration is the main weakness in the data science world, and, with many actively trying to improve the way in which data is shared, the future looks hopeful. The main issue facing companies in the industry is that there are only a finite amount of data scientists, and so the remit is not as broad as with a general social media site.

Gain In-demand Cloud, Data, and Machine Learning Skills with the Full Google Cloud Suite of Learning Programs on Coursera

Online learning leader Coursera now offers the full Google Cloud suite of programs on their learning platform. Learners can enroll in Google Cloud courses and Specializations to access top-quality cloud training. All courses include free hands-on labs to provide practical experience.

Data Scientists Will Change the World — Be One of Them

In this contributed article, Mamtha Parakh, Head of Data Science at Quartet Health, discusses what it means to be a mission-driven technologist, and how can we define and bring this culture to our own tech companies through four different approaches.

Infographic: The Data Scientist Shortage

Statistics point to a promising career in data science for anyone with the skills and interest to pursue this field in the 21st Century, whether one wishes to start from the first year of university or redirect his or her track midway. Given the current employment crisis featured in the infographic below, developed by our friends over at the University of California, Riverside, even individuals who have pursued programming and technical programs at high school could be thrust into more demanding positions in the work place.

Building a Winning Data Science Team

In this contributed article, Brad Cordova, co-founder and CTO of TrueMotion, discusses the importance of building a winning data science team, including actionable tips drawn from his own experience on structure, investment and building a culture where data science thrives.

How Operational Machine Learning is Transforming Industrial Operations

Our friends over at Falkonry just released the new infographic below “How Operational Machine Learning is Transforming Industrial Operations.” It includes some great data on how fast the industry is growing, who is using it (Toyota, Ciner, Honda, Kawasaki, etc.), how predictive analysis works, and applications per market (semiconductor, oil and gas, energy, automotive, mining, etc.).