Remember your first day at school when you were standing in the playground, school bag in hand, desperately looking around the playground to find a familiar face, someone that you could relate to - either physically or mentally? As human beings, our innate desire to belong and be part of something greater than ourselves is a fundamental aspect of our social nature. We yearn for connections, seeking out groups, communities, or organisations that resonate with our values, interests, and aspirations. 

This feeling isn't left at the school gates, as  Raana Saheb Nassagh, Senior Data Scientist, describes how she sometimes turns up to a meeting and is the only female participant. 

Raana's passion for well-written code, intricate software architectures and elegant design patterns is palpable as she talks about her journey into data science and specifically her work with AI models. She wears many hats at work from machine learning engineer to project manager, highlighting how one's skillset doesn't just apply to one role in tech. But, like us, she wants to see more women in these roles and has some really cool ideas on how we can all make this happen...

CAN YOU TELL US ABOUT YOU AND YOUR JOURNEY INTO THE FIELD OF DATA SCIENCE AND WHAT INSPIRED YOU TO PURSUE A CAREER IN THIS AREA?

I was 16 when I had to choose my specialisation at school. I had to answer the question: “Should my main subject be art or math?”.  I remember how I wanted to put the mathematics books away, to go after photography. But somehow, I just couldn’t do it. I just loved math so much … This was the start of my data journey: A passion for solving complex problems and thinking logically. So, I graduated with a math diploma and continued on with studying software engineering. During my bachelor studies, I got fascinated by AI topics like genetic algorithms and neural networks. That was my motivation to continue with a master program focusing on AI. 
Since then, I have worked for 2.5 years as a data scientist, whose everyday work is dealing with data and struggling with pipelines and deployments. And still, I enjoy the moments when we try to solve a problem with mathematical equations and forget the time while brainstorming about different solutions … this is what I like about my job.

WHAT IS YOUR ROLE AND RESPONSIBILITIES AT PLAN D?

Although I have the title „data scientist “,  I fulfil a wide range of roles and responsibilities at PLAN D. Sometimes I am a data scientist, who is working for hours with data, patterns, visualizations, and AI models. Other times I am a machine learning engineer, who deploys the whole pipeline of the AI models and tests the endpoints. There are times when I am a data analyst, who analyses a topic and presents the results to our customers. On some occasions, I also play the role of a project manager and make sure everything is finished on time before the deadline. That is why I prefer the term „full data“- we here at PLAN D do just everything with data :) 

WHAT SPECIFIC AREAS OF DATA SCIENCE AND MACHINE LEARNING ARE YOU MOST PASSIONATE ABOUT, AND HOW HAVE YOU DEVELOPED YOUR EXPERTISE IN THOSE AREAS?

I like many different topics in the data field. However, I come from a software engineering background, so I just love well-written code, intricate software architectures and elegant design patterns. That is why I like to think a lot about the whole architecture of the AI models before I implement them. I have been passionate about this since my last bachelor semesters where I had courses like object-oriented programming and software system architecture. I followed these topics also in my master's study, where I used AI to find anti-patterns in code.

AS A FEMALE DATA SCIENTIST, HAVE YOU FACED ANY UNIQUE CHALLENGES OR OBSTACLES IN YOUR CAREER? HOW HAVE YOU NAVIGATED AND OVERCOME THEM?

The biggest challenge for me is a meeting or video call where I am the only female participant. Then, I sometimes see myself as a lonely wolf and miss seeing other female data scientists, engineers, front-end, and back-end developers. Having women in tech roles brings new perspectives and changes the dynamics of the whole group. Since I have no female role model in the team to look up to for guidance, I try to be the best version of myself. Maybe then I can be a role model for others and motivate other women to pursue a career in the data domain.

IN YOUR OPINION, WHAT ARE SOME KEY STEPS ORGANISATIONS CAN TAKE TO PROMOTE AND INCREASE DIVERSITY IN THE TECH INDUSTRY, SPECIFICALLY WITHIN DATA SCIENCE AND MACHINE LEARNING ROLES?

I think women should be encouraged for tech roles as early as possible, for example at school. Tech companies can encourage young girls for tech roles, by offering free courses, workshops, and talks or internships. 
Somehow the tech branch needs to demonstrate that women are welcome here. Especially in the field of data science, there are a lot of fun programs and software that can be taught at an early age and motivate girls for AI topics.

SR2'S WOMEN ROCK PLATFORM AIMS TO PROMOTE DIVERSITY AND INCLUSIVITY IN TECH. CAN YOU SHARE ANY EXPERIENCES OR INITIATIVES YOU'VE BEEN INVOLVED IN THAT ALIGN WITH THIS MISSION?

As a member of PyLadys, I like to share knowledge with other women, who work with Python. That is why my team and I also host PyLadys events on the 11th of July on our premises.  On this occasion, I also contributed a talk about how to become a better code reviewer. What I especially like about PyLadys is that they are not only open for women but welcome people from all walks of life independent of their background, and thus create a very diverse community focused on Python programming.  

DO YOU HAVE ANY ADVICE FOR PEOPLE THAT ARE LOOKING TO GET INTO THE TECH INDUSTRY?

I think women in general, and I especially, tend to overthink a lot of things. So here is my suggestion: Just do it and don’t overthink it! Send applications even if you might not fulfil all requirements, take courses, even if they seem daunting at first, and do what you like to do. One reason why women are not in tech roles is that they don’t have so many role models to look forward to. So: Be the first one! There is no "wrong" and "bad", there is just "new" and "better“. 

 

Thanks, Raana, you rock 🤘

Interview by Finlay Bright