Next Meetup

Data Scientist Late Fika
TEMA: REDUCING THE GENDER GAP We meet, take a coffee, we get to know ech other, mentor each other and this week we can talk about: WOMEN, OBSTACLES IN THE WORKFORCE: The challenge of getting and keeping women in tech and data science This challenge goes beyond educational exposure though. Recruitment and attrition seem to be other obstacles causing the numbers of women in the field to drop. The NCWIT report questions the common belief that the lack of gender diversity among qualified applicants is the top reason for the unbalanced ratio of men to women in the tech industry. According to a LinkedIn study, more women are hired as software engineers outside of technology, comparing the 20% hired in technology to the 32% hired in healthcare and 25% in banking. Gender diversity could be unbalanced based on the way a company recruits for a position. Many recruiting efforts rely on referrals to determine top candidates. However, according to the NCWIT report, a study by the Federal Reserve Bank of New York found that 64% of employees recommend candidates of the same gender as themselves. And in a 2015 study, Looksharp found women are three times less likely to seek tech internships than men. These internships are another common way to recruit for STEM related positions. Once women do break into the field, keeping them poses another problem. According to the NCWIT, women are two times more likely to quit their job than men in the high tech industry (41% to 17%). However, the primary reason for leaving is not due to family obligations, contrary to popular belief. In the same NCWIT report, it was found that 49% of the women who left their SET job remained in the industry. In fact, 22% of these women went on to create their own company. WHY ARE WOMEN LEAVING? A study by McKinsey and Lean-In asked similar questions of women in the workforce as a whole. They found that women are four times more likely than men to feel like they have fewer opportunities than men in the workplace. Looking at the computing and tech fields, 30% of women in SET positions felt isolated or stalled, according to the NCWIT report. The feeling stems from “having a limited number of important or special assignments that are highly valued by high-level managers,” and “not understanding the ‘unwritten rules’ or norms of [a] company or department,” which can be linked to a lack of mentorship and support. According to a Hewlett study from 2014, this type of dissatisfaction is found more in women ages 25 to 34 who are fresh in the field. During a roundtable discussion, Women in Data Science, the data scientist of Data-Mania, Lilian Pierson said, “Women need to understand what opportunities are available to them, what those opportunities involve, and what the quality of life looks like for someone in this role.” This can’t be achieved without proper support. Mentoring has had a large influence in closing the gender gap in tech and data science. In the Women In Data interviews, almost all of the interviewees mentioned a mentor that they relied on for encouragement to remain in the field, whether a supportive family member or a co-worker open to questions. Sarah Aerni, the data scientist at Pivotal, said in the roundtable discussion, “… One of the main challenges is that mentors are most effective when they can see themselves in those they are helping. I actually do not believe that this means women should only be mentored by women. Instead, I think it has to do with the path that you have taken, so mentors can recognize and help with challenges they faced themselves.” RESOURCES: Women in Machine Learning and Data Science (WiMLDS) – A community hosting events, conferences and workshops for women interested in machine learning and data science. (USA) Women in Big Data Forum – A LinkedIn forum aiming to increase the diversity in the big data field through mentoring and peer engagement. (source: November 2018,

Wayne’s Coffee

Hammarby allé 27, 120 32 Stockholm · Stockholm

What we're about

Women have always been instrumental in technology development. Yet, the amount of women in computing occupations has steadily declined since 1991, when it peaked at 36%.

Why? What do you think? ... Want to take a coffe and talk about it ... or something else? Exchange experiences? Ask/Give advices ...
It would be nice! Come as you are ... (Of course all genders are wellcome)

Do women now have a general lack of interest in Science, Technology, Engineering and Mathematics (STEM) positions? Is there a bias inhibiting women’s success in these roles? Are there cultural elements causing the decline?

The challenge of getting and keeping women in tech and data science goes beyond educational exposure though. Recruitment and attrition seem to be other obstacles causing the numbers of women in the field to drop.

Can we meet? Exchange experiences? Take a beer and you talk ... ?
Come and have a have a beer ...

All genders, you are well come to this meetup, ...

(source: www. )

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