Guest Blog - Women in Data & Technology: Inna Tishchenko, 86,400
Inna is the Lead Data Scientist at 86 400, an Australian digital start-up bank that aims to disrupt the banking scene by putting its customers first.
She holds a Master of Science degree in Mechanical Engineering from ETH Zurich – one of the top 10 universities in the world – and has an extensive experience across a wide spectrum of Data Science applications and industries ranging from big corporates and research institutions like ABB and CSIRO to emerging businesses, covering Finance & Insurance, Robotics & Automation and Health sectors.
Inna is the lead and co-author of five publications in applied Data Science and a recipient of a PhD scholarship award under Australian schema.
What would be the key things that allowed you to get to where you are today and what do you attribute your success to?
I think the key to success lies in recognition of emerging opportunities at the right moment and acting upon them by accepting the associated challenges. Progress also often includes giving up perks such as leisure time, an established state of comfort or job security. For most of my career changes, I had to give up something for what I considered beneficial in the long-term.
A positive attitude is also important. Expecting future success helps to assess the opportunities and challenges arising on a day-to-day basis. Without trust in the future, the obstacles may seem big and rewards uncertain, which is a recipe for maintaining the status quo. In addition, having a picture of the future goal is a good guide when the times are tough, and decisions need to be made.
I firmly believe that it is crucial to enjoy work as it is hard to be successful in a mismatched role. My passion is to solve problems and assist others by providing insights and solutions, and thus Data Science is the best place for me. Further, I prefer the simplest feasible solutions to complex problems, and therefore I am in an industry generating tailored and intuitive solutions based on real-life imperfect data. I have found the job that aligns to my personality, and it gives me opportunities to play to my strengths.
Have there been any career-defining moments?
Coming from a background in Robotics & Automation, I have worked on a variety of projects in Automation Processes and Computer Vision. Nonetheless, I discovered my true passion when I started working in Data Analytics deriving insights from cancer-related data. To me, working in Data Analytics is comparable to playing the intriguing role of a detective attempting to reconstruct a scene by putting clues together in such a way that they all tell the same story.
The emergence of the term ‘Data Science’ has also had a big impact on my career. Data Science has embraced my interests and favourite tools by putting them under one hub, which made it easier for me to outline my professional identity.
What advice would you give to other females looking to pursue a career in Data?
It is probably the most optimal time to join the Data Science community. A few years ago, the term ‘Data Science’ did not exist. Nowadays, it is considered “the sexiest profession of the 21st century” and every advanced university offers a Data-related program. There is a shortage of skilled Data Scientists on the market and I believe it will remain the same for at least a few years, as the number of companies initiating Data-related projects is growing at a high pace.
I also think the profession will become more diversified, and based on my personal experience I would recommend new entrants to the profession take part in a range of projects to find what interests them the most in the field. In Data Science, the application area plays a big role as it defines the project length and respective success measures, which may be more or less appealing depending on someone’s work style and personal interests.
Further, it is crucial for Data Scientists to be collaborative and communicative. Given that women are generally considered strong on that part, it is rather advantageous to be a female Data Scientist.
To hear from other inspiring women in the Data and Technology space, please click here.