#DiversityDrivesData: With the "Women in Data" scholarship for more women in the data industry

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Graphic in the article "Skill Gap Analysis: How Companies Effectively Determine the Training Needs of Their Workforce" shows the StackFuel Data Literacy Assessment (icon image).

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In cooperation with Telefónica Deutschland / o2, StackFuel launched the "Women in Data"Scholarship which finances online training for women to become data analysts worth €2,990 each, including mentoring, under the motto #DiversityDrivesData.

We live in a digital world that never sleeps. Every minute of every day, consumers around the world shop online for $1 million, make 1.4 million video and voice calls, share 150,000 messages on Facebook, and stream 404,000 hours of video on Netflix.1 More data is generated every hour than in an entire year, 20 years earlier.²

This rapid technological progress, which we rarely notice but use every day, is mainly made by men. Just 25 percent of jobs in STEM (mathematics, computer science, natural sciences and technology) are held by women, and in the data industry we get a slim 15 percent. As a result, the female perspective still often comes up short.

Teams that are not diverse often focus on the average man rather than the needs of all genders when developing products or services. For us, that means: It is time to act.

Nowadays, data determines the economic success or failure of companies. Data talents are not only to be found in the IT department, but also in other departments such as marketing, logistics, HR or finance.

Data professionals are more in demand than ever, and becoming a data expert yourself may be easier than you think: To help women* find their way into the world of data and provide them with the skills they need to get started in the data industry, we at StackFuel have teamed up with Telefónica Deutschland / o2 to offer the "Women in Data" scholarship launched, which 50 women further training to become a data analyst enables.

*We use the term "women" inclusively to refer to all people who identify as women. While this scholarship is explicitly aimed at women, all non-binary or genderqueer people are also invited to apply to apply.

Click hereif you would like to find out more about the job of a data analyst, typical tasks, salary and career opportunities.

Why the data industry needs more women

"We cannot design a world that works for everyone without women," wrote British author Caroline Criado-Perez in her book "Invisible Women: How a World Dominated by Data Ignores Half the Population."

The IT sector is considered one of the fastest growing industries and already today there are more unfilled IT positions than graduates to meet the growing demand of the labor market. Although young talent is so urgently needed, according to one Accenture Study the number of women in this field will continue to shrink over the next ten years. Promoting diversity in such teams therefore by no means means fewer men; it means compensating for the shortage of skilled workers by also promoting the qualifications of other groups in society.

"There are numerous competent women who would be a real asset in this subject area," says Nicole Gerhardt, Chief Human Resources Officer at Telefónica Deutschland / O2. "We want to actively break down barriers here with new approaches such as the Women in Data scholarship and specifically encourage women to continue their education in future-relevant professions."

What many don't know: The first person to develop an algorithm was a woman, Ada Lovelace, a British mathematician. Despite all this, even today, almost 200 years later, many women still don't trust themselves with a technical profession. The fears of mathematics and the broad field of programming are too great. Yet women are particularly suited to professions such as data analyst, which require so much creativity, detail orientation and communication skills.

The job as a data analyst is not only varied and offers versatile, professional opportunities, but is also fun. The reluctance that has existed up to now will become a fundamental challenge, especially for business, if women are not actively promoted. Therefore, this promotion is not about favoring women, but about pushing the development of mixed-gender teams.

The full scholarship is intended to qualify women to work with data and thus ensure more diversity and new blood in data teams. The 50 identified winners will receive online training to become a data analyst including mentoring from StackFuel with a total value of 150,000 euros for the year 2021.

Promoting equal opportunities and diversity

Many jobs typically done by women are lower paid and less recognized than male-dominated occupations. Although many women are employed, about two-thirds of household chores and family management are still done by women today. Time appropriately headlined in 2019 that women work 4.5 hours³, unpaid, every day.

We can't change these unequal circumstances in a day, but we want to take them into account and actively remove barriers. We strongly believe that all women - regardless of financial status or their background - should have equal opportunities to pursue a career as a data scientist.

The Corona pandemic in particular seems to have left its mark on equality: By the end of 2020, about one million more women will have lost their jobs than men, making a total of 5.4 million women.4 That's one more reason why we want to specifically promote women. Not only do we want to make it easier for them to return to work, but we also want to give them the great flexibility that their everyday lives require. Because if these women are overlooked, companies will also miss out on valuable talent.

With the scholarship, we want to contribute to increasing the proportion of women in tech and data professions to at least 50 percent and make it the new normal. The four-month, part-time training course to become a data analyst, worth €2,990 each, has a special focus on the Python programming language and includes professional mentoring that prepares participants for their future job roles in a practical way.

In addition, the Data Analyst Training is so flexible in terms of time that each woman can decide for herself when and how much time she can devote in a day or in a week. In order to attract as many women as possible to the scholarship, it is offered not only in English, but also in German. This makes the "Women in Data" scholarship currently the only German-language scholarship for women on the topic of data in the DACH region.

In addition to the in-service training to become a data analyst, the scholarship winners are accompanied by professional mentoring, which on the one hand ensures learning progress and on the other hand gives the women the opportunity to ask questions and exchange ideas with the other winners at any time.

The learning content is particularly hands-on with interactive formats, real-world business cases and coding challenges, preparing participants for their future job role as a data analyst. However, the fellowship is also suitable for participants who want to incorporate working with data into their current job. No major prior experience is required to participate.

"Data analysis is one of the most sought-after skills of the decade. Experts who can handle data are in demand in almost all specialist departments, such as marketing or finance. With our online trainings, we offer women targeted data skills and thus directly contribute to more equal opportunities and diversity in Germany's digitalization," says Leo Marose, CEO and Co-Founder of StackFuel.

Diversity brings numerous benefits for all parties involved. In its report, McKinsey was able to "Delivering Through Diversity. from 2018 show that mixed-gender teams are 33 percent more likely to be profitable. A Study of Harvard University came to the same conclusion and also found that diverse teams were able to achieve better results than same-sex groups - regardless of whether they consisted only of men or only of women.

This awareness already exists in many companies and is actively promoted. In order to sustainably strengthen diversity in STEM fields, it is important to eliminate existing prejudices that boys and men are superior to girls and women in technical matters. An important means of achieving this is to create role models and thus shape a new, sustainably diverse image of occupational profiles.

Get to know our Women in Data

Data expertise has many facets. It is just as colorful and varied as our own Women in Data and their careers. These women are inspiring role models for us and they have proven that the path to the world of data does not always have to be the same. It is diversity that drives the world of data.

Laura-Luisa Velikonja is a Senior Data Scientist at Telefónica Deutschland. There, she uses machine learning to help the various business units make better and faster decisions.

"People who give boys and girls early motivate and support, are critical to motivating them equally to pursue these all-important career fields."

Learn more about Laura's way.

Dr. Yen Hoang is an Educational Data Scientist at StackFuel. Yen was born in Ho Chi Minh City, Vietnam and came to Berlin with her parents when she was four years old, where she grew up in Friedrichshain.

"Believe in yourself. Be strong. And remember how much you have already achieved. Then you'll realize what else you can achieve. Just take the first step."

Learn more about Yen's way.

Dr. Verena Braunschober has been working as a Senior Data Analyst in the Data Analytics & Artificial Intelligence department at Telefónica Deutschland in Munich for almost nine years. In this interview, she talks about how she developed her passion for data and how StackFuel's training has helped her on her career path.

"Being visible and making your voice heard to be involved in decision-making, sometimes that just takes a little bit of practice and courage."

Learn more about Verena's way.

Many companies now place great emphasis on recruiting, retaining and developing female talent for their IT and data departments. However, this is not where the efforts should end. In our fast-paced working world, it's important to have the right qualifications and in-demand skills to advance your career and stay on the ball. In the "New Work" we never stop learning.

Data analysis skills are in such high demand because they are so universal. They qualify for far more than just the job of data analyst, but are of great advantage in numerous specialist departments and job roles, and are becoming increasingly valuable as digitization and datafication of all areas of life progress.

With the scholarship to a new career

Who can apply for the scholarship

In particular, we want to encourage women to join the data industry and apply for the Women in Data Scholarship. apply. To participate, you should be a woman:

  • Be at least 18 years or older
  • Have your domicile or permanent residence in Germany, Austria or Switzerland
  • have a good knowledge of German or English at least B2 level
  • have a basic understanding of mathematics and statistics, which we ask for in a short aptitude test
How to apply in 3 simple steps

To make the selection process as fair as possible and to make sure that you are the right candidate, we need in Step 1 some application documents from you, which you can find on our Application page can submit. This includes your CV (1-3 pages as PDF), a proof of your language skills (in case you are not a native speaker) and either an application text (max. 250 words) or application video (1 to max. 2.5 minutes long) answering the following questions:

  • What interests you about data?
  • What has prevented you from pursuing further education in data so far in your career?
  • How would you like to use your scholarship for you and your career?

Tell us more about your background and also let us know if you are planning a career change, are in a situation of economic hardship (e.g. low income or similar) or if you consider yourself to belong to a social minority or disadvantaged group (e.g. due to a disability).

In Step 2 you can upload your documents or your video and Step 3 a short placement test is waiting for you, which should only show us the level of your previous knowledge. So you don't have to be afraid of highly mathematical formulas. After that, we will review your documents in an objective selection process and, at best, contact you as the winner on June 21, 2021.

If you are still interested in the scholarship at that time, you will start your Data Analyst training with the other 49 Women in Data on July 05, 2021. Depending on how you want to allocate your time to learn, the training will last between four weeks (part-time) and four months (in-service).

We firmly believe that all women should have the same opportunities to pursue a career as a data analyst. Whether you believe you are at a disadvantage or not, whether you are already working in a data-related environment or starting your career as a career changer - with us you get the chance to sharpen your data skills and shape your career path.

Do you still have open questions? We have collected the most important information and most frequently asked questions on the scholarship website. Here you can find our FAQs.

Take your chance - until June 10, 2021

The data industry needs you! Are you ready for a data career or to get started in your job with data-driven, analytical work? Then visit us at https://scholarship.stackfuel.com/ and apply for the "Women in Data" scholarship.

About Telefónica Germany / o2: Telefónica Deutschland offers mobile and fixed-network services for consumers and business customers. With more than 44.3 million mobile lines and 2.4 million broadband lines, the company is a leading integrated telecommunications provider in Germany.

No network operator connects more people with mobile communications in this country. Telefónica Deutschland Holding AG has been listed on the Frankfurt Stock Exchange (MDAX) since 2012. In the 2020 financial year, the company generated revenue of 7.53 billion euros with just under 8,200 employees. It is majority-owned by the Spanish telecommunications group Telefónica S.A.

About StackFuel: StackFuel is Germany's leading provider of certified online training and retraining in Data Literacy, Data Science and AI, tailored to the needs of companies in industry and business. To address the digital transformation and the upcoming skills gap in data and AI, StackFuel helps companies effectively and efficiently develop employees into future job roles.

The innovative online training courses offer participants a modern and flexible learning experience with an interactive and cloud-based learning environment in which they independently develop algorithms using industry data sets.

Sources:

1Domo (2020): "Data never sleeps" [03.05.2021]

²Seagate (2020): "Rethink Data Survey" [03.05.2021]

³ Time Online (2019): "Women work 4.5 hours a day without pay". [03.05.2021]

4 National Women's Law Center (2021). "Women's labor force participation hits 33-year low" [05.05.2021]

World Economic Forum (2021): "Global Gender Gap Report. [05.05.2021]

Training Industry (2021): "The Time Is Now: 3 Ways Learning and Development Can Support Women Reentering the Workforce." [04.05.2021]

Forbes (2020): "Top Three Reasons We Need More Women In Tech." [22.02.2021]

Accenture (2021): "Cracking the gender code" [23.02.2021]

McKinsey (2018): "Delivering through diversity" [23.02.2021]

BCG (2017): "The Mix That Matters" [23.02.2021]

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