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Article written by Lydia Brand, Data & Analytics Consultant at X4 Technology.

I had a fantastic interview with Jill Mambetova, Partner & Data Scientist at Insight Specialists, a consultancy specialising in providing creative strategies and solutions to drive business growth by utilising cutting edge technology.

It’s not uncommon to experience a moment when you question your ability to do a project at some point in your career, and one of the biggest lessons Jill learned was that having the ability to control your thinking and channel it in the right direction is as an important factor in succeeding.

This interview is filled with interesting insights into Jill’s career, her experience of being a female in a male dominated industry and her thoughts on some of the key challenges faced by data scientists in her industry right now.

What’s been the most memorable moment in your career to date?

I was working on one particular data science project and it definitely pushed the limits of what I knew. I had this feeling that I wasn’t going to be able to complete it and I could feel panic slowly kicking in. Up to that point, I’d never really experienced that kind of sinking feeling because I always felt confident in my analytical ability.

That was the first time that feeling had dawned on me but before I completely lost myself, I said to myself “ok, hold on, let’s think about this in terms of solutions”. This focused my brain, switched the gears and allowed me to look at all the possible options and break down how they can be achieved in smaller steps, working them slowly one by one. That approach definitely helped me to calm down and solve that problem.

The main lesson I learned that day was that while knowledge and experience do matter in your success, your ability to control your thinking and channel in the right direction is clearly an important factor in succeeding.

What kind of improvement, change or growth are you trying to achieve at Insight Specialists?

The Insight Specialist is a partnership made up of three founder women specialising in data science, analytics and finance. We came together to build something completely new and we have big plans to incorporate AI and the new communications technologies to deliver disruptive business solutions for the job market.

The tool we’re working on and hoping to deliver in Q1 is called Quengi. It will provide multiplatform communication with candidates and will enable the use of all data points about a candidate to increase conversion and position matching.

The idea is to standardise and streamline mundane admin tasks, and provide candidate pre-matching instead of manually sifting through 100s of CV’s. We are aiming to attract top talents to the platform by reducing time to fill and offering personalised recommendations in terms of career development and recruitment options.

What are the biggest challenges facing data scientists right now in your industry?

I think there are 3 main challenges, the first being credibility and a lack of understanding of how AI influences our daily decisions. I think for the majority of people data science and AI is an abstract notion, and it is not accessible to wider customer base in terms of understanding how it works and its actual impact that’s already taking place. Lots of education and increase in accessibility needs to take place.

Second is the use of data science in small and medium businesses, as it has proved to drive revenue and does not have to be expensive to implement and benefit from it. This wider adoption at grass root levels will enhance the credibility of the data science greatly and allow it to grow in an even bigger space.

And the third is the lack of comprehensive and accessible training opportunities for existing specialists to transition into data science. There are tens of thousands of analysts who potentially could be doing data science but it’s not easy while you’re doing an analytical job to study and become a data scientist. Ultimately, the whole analytical profession is going to move into data science, where you need to be able to make more complicated solutions and build working pipelines and data science solutions. Widely accessible training opportunities and systematic workplace training should be a must for all companies wanting to move forward and benefit from the data.

Reports show that as few as 15% of data scientists are female. What advice would you give to businesses who are struggling to attract and retain senior female talent?

When you’re a female data scientist, what I’ve noticed from my experience is that when you sit at the table where most of the colleagues are male, it’s harder to be visible. You need a special approach because we females tend to speak less or let other people speak first, and there are a lot of interruptions that happen around the table so it’s not always easy to handle.

I like the example of Kamala Harris saying to interruptions “I’m speaking!” and that kind of tone and opportunity should be allowed a bit more. But, I know often interruptions will happen anyway, so it’s also about educating people and leadership about listening more.

The second point which hinders a lot of women is that a decision about hiring someone into a higher position is solely made on past experiences and a quite stringent specialism based knowledge, I think selection criteria needs to be softer and wider and cover ability to learn, build teams and create cohesion within an organisation. This way all of a sudden a lot more women become eligible and qualified.

And, finally of course it would be great if businesses paid attention to internal female analysts and let them grow naturally within an organisation by offering comprehensive training and allowing them more managerial level decision-making about self-direction or independent decision-making.

“Data science has an image problem.” This has been said a lot in the news recently, what would be your advice to employers who want to change this perception and create a more inclusive culture in their business?

Inclusivity is definitely growing, I’ve seen a more diverse colleague base but there is still a lot of work that needs to be done. For example, offering extensive training programmes and starting very early on, even at schools, to instil that feeling of accessibility to a data science career path and showcasing the practical and far-reaching aspects of the industry would definitely help.

And specifically for girls, STEM initiatives needs to incorporate data science and emphasize the positive impact and ground breaking changes it can bring to the society as a whole and to a specific individual. There are a lot of exciting developments which children can be drawn to like self-driving cars, robots creating pieces of artwork, chatting to a robot assistance etc.

What excites you most about recent developments and the future of data science and AI?

Some of the interesting developments will be the ones that will answer the latest global challenges that humanity is facing and also dealing with the reality of a post Covid-19 world.

Healthcare and pharmaceutical is one area which has benefited greatly and will keep benefiting at an increasing rate from AI and data science solutions.

I also think that remote working, isolation and loneliness and increase in care requirements for the vulnerable groups is another big challenge which AI can help to tackle by using latest communication technologies, intelligent alert systems, health state assessments, offering robotic solutions, etc.

And there is a challenge like climate change, where AI has only started making an impact, it will require joint global efforts to develop a system of solutions which will have a significant impact starting from tracking, use of geo-satellite imagery, evaluation, alert systems, guiding optimal production and distribution and so on and so on. Opportunities are limitless! We just have to remember that AI and Data Science are not a replacement for our actions, but enablers and can maximise our actions manifolds, I hope these will be only positive ones to benefit humankind overall.

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