Weltfrauentag 2021: Interview mit 9 weiblichen Data Heros

The future is female. Die macht auch vor Data Science Teams keinen Halt. Zurzeit ist nur etwa jeder sechste Data Professional weiblich und es liegt im Interesse von Unternehmen und der Gesellschaft, die Geschlechtervielfalt in Datenberufen zu fördern. Unternehmen suchen aktiv nach mehr weiblichen Data Scientists für ihre Teams und dabei wollen wir helfen. Deshalb haben wir neun inspirierende „Women in Data“ zu ihren Erfahrungen, Learnings und Ratschlägen für weibliche Newcomer befragt.

Caroline Kleist, Head of Data Science, Positive Thinking Company GmbH

What do you love about working with data/in data science? 

Working with data and data science demands so many different skills and always brings up new challenges. It’s probably one of the most diverse jobs you can do at the moment. I love that we’re all working together at the edge of innovation and implementing things that have just been released from research directly into the real world. Together we’re transforming our everyday lives and our companies with the newest and fanciest topics you can get your hands on – how exciting is that?

How did you get started in the industry?  

The obvious answer is that I studied statistics and I always enjoyed working with data so I started working in tech in 2015. Back then, there wasn’t actually even a job description for “Data Scientist” in Germany and to be honest – I was just really lucky to start in this industry shortly before it became so hyped and I’m very grateful for that fact. The less obvious answer is that as a child I always had all options: my parents gave me both dolls and steam machines to play with, thus laying the most important cornerstone for my career in tech. It never mattered whether I was a boy or a girl.

Why do you think that more women should work in tech and data science? 

Besides coding, math and all the technical skills there’s a very important superpower you need to successfully deal with data and tech projects in general: namely empathy and strong communication skills. I am not a friend of attributing certain characteristics to men or women because we are all individual, but us women are said to have a lot of empathy and good communication skills, right? So let’s use them! My own career got a big boost, not despite but because I’m a woman. And not because of gender quotas, but because of this instinctive feeling for people and their concerns that you need in difficult and complex projects. For example, when you want to establish a new culture around the use of AI and machine learning in a company you’re most probably confronted with silos and more closed structures in companies. In order to be successful with this mission, everyone involved has to have conviction. Women often have a special sense for this and anticipate the need to explain the results or algorithms to everyone in such a way that everyone understands and is convinced in the end. This skill is really needed in our data science projects and that’s why I wish there were more women in tech and data science.

How do we get more women excited about careers in data? 

We really have to stress the need for empathy I just mentioned that’s urgently needed for data science and tech projects. And of course, besides that we must continue to encourage girls to be curious about science subjects and choose them at school and university and not shy away from them. The more role models there are, the more likely we are to inspire little girls, so let’s talk about our stories and share them.

Do you have any tips for women who want to gain a foothold in the industry?

Be yourself and be confident about it! Don’t waste any thought or energy thinking about whether someone might think your competence or abilities are inferior just because you’re a woman. If you don’t have doubts about your abilities, then your environment doesn’t either. It goes without saying that women work in tech and that starts with you.

Dr. Nina Meinel, Strategy & Data Science, Syncier GmbH

What do you love about working with data/in data science?

It’s the data itself, so understanding what the data is about, how and what is being measured and how the data can support a business case. And of course all the fun stuff along the way, tools, programming, visuals, and model evaluation.

How did you get started in the industry?

My love for data came simply with studying statistics at university. The courses where really cool and there were two great departments for statistics and econometrics even one already teaching in the 90s.

Why do you think that more women should work in tech and data science?

It’s about bringing new fresh creative ideas and thinking into tech and data. Women see things differently, argue differently and might offer another cool solution. Especially in data and science, a lot of it is about having good discussion, finding solutions together and this only happens when you listen to everyone.

How do we get more women excited about careers in data?

A love for numbers and tech is something that starts pretty early. Having some programs in school would definitely help as well as more female teachers or female data scientists teaching and providing courses.

Do you have any tips for woman who want to gain a foothold in the industry?

Never stop being curious, try out new stuff, ask question after question, because you need to understand. And believe in your own abilities, because you can definitely do it.

Dr. Yen Hoang, Educational Data Scientist, StackFuel GmbH

What do you love about working with data/in data science?  

Working with data is like speaking a language. The different applications are just dialects. My background is in the medical field but I can quickly understand the critical points when discussing different analytical approaches for sales or tracking data, for example.

How did you get started in the industry?   

One of my first work experiences was analyzing next generation sequencing data of a breast cancer patient whose cancer treatment did not achieve the expected results. So, I had to find the few genes (out of 25,000) which were mutated so that the doctors could go further with an individualized targeted gene therapy for that patient. I was so afraid to make mistakes but at the same time also thrilled and honored. I was totally hooked on data science!

Why do you think that more women should work in tech and data science?

There’s no reason why they shouldn’t. At the moment, we’re still under-represented and in an ideal world I think the numbers should be even. Women have a different point of view and taste in technical devices and tools compared to men. So, it’s important to include women in coding the tools that everyone uses.

How do we get more women excited about careers in data? 

There are several steps that we can take. I genuinely think it starts in the first years of childhood. Parents should stop gendering their kids and buying barbies for girls and fire trucks for boys. It’s important to encourage girls more to get them excited about data and programming in school. In the professional world I think a certain quota for female representation in tech and data departments of a certain size should be required by law. Why only in leading positions? If we start living in the ideal world, children can see and experience that it’s common for women to work with data. And after one generation this quota will be redundant. However, I believe it should also work the other way around, e.g., more men should be encouraged to go into nursing.

Do you have any tips for women who want to gain a foothold in the industry?

It’s hard to land a tech/data job if you’re a woman, no doubt. Been there, done that. It’s important to not undervalue yourself. Believe in yourself. Be strong. Remind yourself (maybe even on a daily basis) that you’ve achieved a lot. And don’t be shy with your certificates and your GitHub repos. In this field, your code tells the story of your hard work.

Irmantė Ežerskytė, Product/Project Manager at DB Training, Learning & Consulting

What do you love about working with data/in data science?

As the data field is quite new for me, I’m excited to learn how many possibilities the effective use of available data opens up in any industry. I have a background in social sciences and from a social perspective I find it extremely interesting, for example, how the right data visualization and narrative influences the human perception.

How did you get started in the industry?

I would say that data industry found me rather than the other way round. I encountered this industry after starting my new position as product manager at DB Training and data courses are a part of my portfolio. This challenges and motivates me to learn new things at the same time.

Why do you think that more women should work in tech and data science?

The technology field is constantly growing and offers a lot of opportunities for women and men alike. I think that getting more women into this industry could also bring new perspectives to the field of data and the development of new technologies.

How do we get more women excited about careers in data?

I believe that it’s hard to push someone into a particular field. However, attractive training and education possibilities within a company could enable a deeper understanding of the field and promote it as a career path.

Do you have any tips for women who want to gain a foothold in the industry?

Just leave your comfort zone and try out new things, if you’re interested.

Laura-Luisa Velikonja, Senior Data Scientist, Telefónica Germany GmbH & Co. oHG

What do you love about working with data/in data science?

I love many things about being a Data Scientist, but the one I love the most is definitely the versatility. Versatility in terms of topics, methods, tools and even people. This job never gets boring and every day I learn something new. And in creating data products, there are interfaces with many different disciplines such as software engineering, operations, legal, of course the customer we are creating these products for, management, and so on. Getting to know these people and how they work and collaborating on a product in a very interdisciplinary way makes me really happy.

How did you get started in the industry?

During my math studies, we were told that you can do anything with math but deciding on a discipline was pretty hard for me. I was already a generalist by then, trying different student jobs and different industries. I felt like I could do a lot of different tasks with data science, which turned out to be true. So I started my career with a traineeship at a data science consultancy in Munich.

Why do you think that more women should work in tech and data science?

I firmly believe that diverse teams in any industry produce better results because different perspectives help teams be creative and tackle problems in an increasingly complex world. Unfortunately, there is still a long way to go in the tech industry when it comes to gender diversity. That’s why we should really work on getting more women, but also more diversity in general, into the tech and data industry. There are huge ethical and moral questions arising in the data field for which we need as many different perspectives as possible.

How do we get more women excited about careers in data?

In my opinion, data jobs are super exciting and everyone I tell about my work is excited, but people are afraid of the math and coding component. So that’s the thing we need to look at. And we need to start early! We need to get young girls excited about STEM subjects, not scare them or tell them what girls and boys are expected to do well at. And of course, role models are important to show young girls that women also love math and coding and work in tech jobs.

Do you have any tips for women who want to gain a foothold the industry?

There are so many roles in the tech and data industry. For most roles, you don’t need  years of programming experience. So, find out about the different opportunities, find something that matches your interests and talents, and then just go for it.

Svenja Plaumann, Training Operations Manager, StackFuel GmbH

What do you love about working with data/in data science?

Learning about the world of data and data science is rewarding in many ways. Data plays such an essential role in our lives now. Acquiring basic data skills should be on everyone’s agenda – these skills can certainly help to put things in perspective.

How did you get started in the industry?  

In a world increasingly based on data, I was fascinated by the idea of being able to help people acquire the skill sets necessary for this. Working at StackFuel has given me the opportunity to actively participate in the digital transformation of professional education.

 Why do you think that more women should work in tech and data science? 

Women make up about 50% of the population but only a fraction of them work in tech or data related fields. Motivating more women to work in data science is critical for ensuring that unbiased and diverse data is available. We need to actively burst male dominated data bubbles and bring unique and diverse perspectives to the table.

How do we get more women excited about careers in data? 

By encouraging women to take up careers in data science now, we create role models for all girls and women of the future. Women in data should be the norm – not the exception. Data is biased because female perspectives and issues are still often not represented or are actively excluded. We can change this – by claiming our right to participate!

Do you have any tips for women who want to gain a foothold the industry?

Ask questions, challenge norms and use data to prove them wrong!

Ricarda Heim, Data Analyst, SKIM

What do you love about working with data/ in the field of data science?

I love the unambiguousness of numbers. There are countless ways of interpreting words, but with data, it is usually a pretty clear story.

How did you get started in the industry?

After doing my master’s in economics & econometrics, I knew that I wanted to work in an analytical job. Starting as an Analyst is a great way of getting an introduction to different methodologies and approaches as well as working with big data sets in general.

Why do you think that more women should work in tech and data science?

It’s a field that’s suitable for anyone who’s interested in data and the insights it can provide. And women are just as skilled at this as men. Since we’re gathering more and more data every day, we will need more and more people analyzing it, getting actionable insights and turn it to good account.

How do we get more women excited about careers in data?

I believe it’s important for young women to see that tech and data science are not and should not be boys’ clubs. It’s for anyone who loves to research, find answers to questions and explore data sets. The knowledge and experience you gain are also often transferable to different industries which brings many opportunities.

Do you have any tips for women who want to gain a foothold the industry?

Data is everywhere today, so make sure you know what you want to do with it. What are the fields or products that interest you? What would you like to achieve or do with data? Do you want to work for one company or an agency with different clients from various industries? Then work on the required hard skills.

Anna Peeck, Freelancer for Agile Project Management, Axel Springer National Media & Tech GmbH & Co. KG

What do you love about working with data/ in the field of data science?

I love that by working in tech, I’m part of the fastest changing and most relevant industry of current times. This means it’s always exciting and thrillingly fast-paced, but I feel that  I have more opportunities than in any other field to also shape this change myself and influence the direction of where we’re headed tomorrow.

Isabel Sum, Account Executive, StackFuel GmbH

What do you love about working with data/in data science? 

I love the variety and possibility data science brings to the table and how it helps us solve previously unsolvable problems faster, cheaper and better.

How did you get started in the industry?  

I first came into contact with software and IT during my dual studies where I worked at IBM in various departments and positions. Later I got the chance to experience and get involved with the fast-paced and ever-changing AI and tech landscape in Shenzhen China, which further sparked my interest in the field.

Why do you think that more women should work in tech and data science? 

I think more women should work in tech and especially data science because diversity helps us to eliminate biases – both human and machine ones.

How do we get more women excited about careers in data?

I think it’s all about awareness and the community. People generally like to surround themselves with others who are similar to them, so we need more role models and more visibility of women in data to break the stereotypes and make it an attractive field for everyone.

Do you have any tips for women who want to gain a foothold the industry?

I would encourage women to join communities, roundtables and information events around the topic of data and AI and to network there. Also, there are so many open positions in the field, and it helps to get a good overview first of which industry or specific area you want to work in and then just start from there and work your way towards where you want to be.

Die Technologiebranche braucht Dich!

Die Technologiebranche legt mittlerweile viel Wert darauf, weibliche Talente zu rekrutieren, zu halten und weiterzuentwickeln. Das ist ein wichtiges Signal, aber die Bemühungen sollten hier nicht enden. In unserer heutigen Arbeitswelt ist eine Qualifikation mit den richtigen Fähigkeiten zur richtigen Zeit entscheidend, um die eigene Karriere voranzubringen. Data Science und Data Analytics sind massiv nachgefragte Fähigkeiten. Wir ermutigen Frauen dazu, spannende Karrieremöglichkeiten im Data-Science-Bereich wahrzunehmen. Derzeit machen Frauen nur etwa ein Sechstel der Arbeitskräfte aus, die mit neuen Technologien arbeitet. Wir sind fest davon überzeugt, dass die Branche mehr Frauen und mehr Diversität benötigt, um Teams zu stärken und innovativer, vielfältiger und produktiver zu gestalten.

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Laura Redlich
Laura Redlich
Als waschechte Berlinerin hat sich Laura schnell der Kreativszene angeschlossen. Nach ihrem Bachelorstudium in Medien- und Kommunikationsmanagement an der Mediadesign – Hochschule für Design und Informatik, war Laura nebenbei beim Film als Booker tätig und später als Produktionsassistentin. Gestartet im Marketing hat sie bei MyToys im Bereich E-Mail-Marketing. Zuletzt war Laura im Content Marketing bei IQPC und konnte bereits Big Data und AI-Luft schnuppern. Privat brennt sie für ein nachhaltiges und achtsames Leben – ob veganes Essen, Meditation oder Yoga - Laura probiert immer gerne Neues aus, um sich weiterzuentwickeln.

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StackFuel ist Deutschland führender Anbieter für zertifizierte Online-Weiterbildungen und -Umschulungen in Data Literacy, Data Science und KI. Zur Bewältigung der digitalen Transformation und der bevorstehenden Qualifikationslücke im Bereich Daten und KI unterstützt StackFuel Unternehmen, Mitarbeitende effektiv und effizient in zukünftige Jobrollen weiterzuentwickeln. Die innovativen Online-Trainings bieten Teilnehmenden eine moderne und flexible Lernerfahrung mit einer interaktiven und Cloud-basierten Lernumgebung, in der sie mit Industriedatensätzen selbstständig Algorithmen entwickeln.

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