Tip for Women in Tech

Takeaway: Women are vastly outnumbered by men in technological fields, which is why networking, mentoring and advice from other women in the field can be invaluable tools.

The gender gap that persists in tech career paths remains an obstacle to overcome for women who want to break into the field. But it can be done, and women who have made it have some valuable insight to share with those aspire to follow in their path or blaze their own. It all comes down to overcoming self-doubt and moving fearlessly forward. A number recommend connecting with others for support, but sometimes the motivation has to come from within.

Fortune Favors the Bold

Sophie Knowles, Founder & CEO of PDF Pro goes this far: “Do not be afraid to start your own business. A lot of people are scared by the prospect of going out on their own, but there is so much opportunity.” Her recommendation is to follow your passion because “you will have a much greater sense of purpose and see that you are capable of so much more than you ever thought you were.” That doesn’t mean just following your heart, though. She adds on the necessity of persistence, as well as doing the requisite research and asking for help when needed.

Likewise, Nancy Wang, Founder and CEO of Advancing Women in Product (AWIP) tells women, “If you see an opportunity you think is a fit, take the risk. Changing careers or taking on a new job can be scary, but never be afraid to take that job that you’re really excited about.” 

Read more in Top Career Tips for Women Working in Technology

Tips for Aspiring Data Scientists

Kaggle graph

Data scientist ranks as the best job for 2019 in America on Glassdoor. With a median base salary of $108,000 and a job satisfaction rank of 4.3 out of 5, plus a fair number of openings predicted, that is not surprising. The question is: What does one have to do to get on track to qualify for this job?

To find out, we looked for the advice given to those who seek to get on this career track. Much comes down to the hard skills in coding and math. But that strong computation alone doesn’t cut it. Successful data scientists also need to be able to speak to business people on their own terms, which calls for the capabilities associated with soft skills and leadership.

Read more in 12 Key Tips for Learning Data Science

To certify or not to the certify: the building blocks of a blockchain career

It’s clear that tech pros in a variety of industries are examining the implications of blockchain. After all, the technology can be leveraged not only for cryptocurrency (i.e., Bitcoin), but everything from “smart” contracts to secure, distributed ledgers. Can developers prove that they have the skills to work with this technology?
Read more in Can You Obtain Certifications for a Blockchain Career?

Data Scientist Interview

Domingos Lopes is about to begin a new job involving machine learning at Google after having completed the NYC Data Science Academy 12-Week Data Science Bootcamp. He came in with a strong math background, having earned a PhD in that field from NYU in 2016. After deciding that he did not want his job prospects to be limited to academic settings, Lopes decided that the best course of action was to acquire data science skills. In addition to the technical skills like Python fluency, he expects to draw on the ability to communicate data insight and work effectively in a team setting as he embarks on his career at Google.

Read more in https://www.switchup.org/blog/alumni-spotlight-domingos-lopes-hired-at-google

Data science training to fill the skills gap

 Datanami article looked at various estimates about how many more data scientists from firms like Gartner and McKinsey to arrive at a range of 100,000-190,000 shortfall by 2020 and 2017, respectively. That's about 60% more demand than available supply in the US. The upside is that salaries for those jobs go up, but the downside, of course, is that the businesses cannot progress on the data front as much as they would like to without the skilled people in-house.

The obvious solution to that problem is to get more people qualified for these jobs. If they didn't learn the skills in college programs, they can now get trained in specialty programs like the NYC Data Science Academy (NYCDSA). Vivian Zhang, the CTO of the school, set it up specifically to meet industry needs and get people the data science training needed to fill those open job slots.

Read more in 

Mind The Gap: Minting New Data Science and Analytics Professionals

The problematic assumptions of resume advice

"Would you tell a prospective employer that you detest people and would rather be left alone in a cubicle all day? " In truth many people would prefer the privacy and solitude to allow them to  focus on their work. It's not that they detest people necessarily but that they do their best work without the distraction of others talking to them. That's the case for introverts who really do tend to be detail-oriented and careful about their work. What many businesses and schools fail to grasp is that you can't usually get social butterfly and efficient on one's own in the same person.

That's the comment I wrote on 5 Words You Should Never Use In Your Resume. Actually I've seen a number of job descriptions that demand both a teamplayer and someone who can work autonmously. Sure, many people can do both, but they would have a preferred mode, just like I can use my left hand but would be using my right most of the time.


related posts: http://writewaypro.blogspot.com/2016/02/save-me-from-resume-advice.html

 http://uncommoncontent.blogspot.com/2012/04/working-alone.html
http://uncommoncontent.blogspot.com/2014/12/views-on-boundaries.html

What were you hired for?

This is my rejoinder to "Don't ask me to think. I was hired for my looks."