"Over the past two years, my role has shifted to supporting the data scientists in the ACES R&D team on advanced analytics projects, ranging from automation of data analysis and modelling to deep learning, web data, text and voice analytics. My main responsibilities lie in the definition and design of modelling methodology to unlock insights and inform decision-making."
Daniela Kolusheva, Data Scientist, Analytics Center of Expertise (ACES), Sofia
What has your career journey been at Experian?
I joined Experian as a Solutions Analyst in 2014. For the first couple of years after becoming part of the analytics group in Sofia, I worked on credit risk and fraud projects across different markets in EMEA. I also consulted on statistical modelling for Basel regulatory projects for several large European banks. After I was promoted to Senior Solutions Analyst, I had the amazing opportunity to lead the restructuring of the core mentoring and induction training process for my team, ACES.
Over the past two years, my role has shifted to supporting the data scientists in the ACES R&D team on advanced analytics projects, ranging from automation of data analysis and modelling to deep learning, web data, text and voice analytics. My main responsibilities lie in the definition and design of modelling methodology to unlock insights and inform decision-making.
Before joining Experian, I conducted research and taught statistics for more than 10 years at major academic institutions in the US and Europe. The switch from the academic world to Experian was surprisingly easy and very gratifying. I kept the freedom to come up with new ideas while at the same time gaining access to our cutting-edge data processing facilities and many interesting real-world applications.
What makes someone a good fit at Experian?
I think the one crucial ingredient to be a good fit at Experian is a growth mindset. We work in a very dynamic environment with a lot of unresolved challenges. The ability to view obstacles as a chance to learn and solve problems has been my go-to recipe for success.
Easily collaborating with people with diverse backgrounds is also a must. My team works daily with a variety of different stakeholders and we need to be able to communicate effectively with all of them to be successful at what we do.
What opportunity for career progression is there?
I believe there are a lot of opportunities to change career paths and pursue your passions within Experian. This has certainly been the case not just for myself, but also for a lot of my co-workers. From the group of peers which started within the same analytics group around the time I joined Experian, some went into consulting, some went on to assume team management responsibilities and yet others pursue careers as project managers or analytics engineers.
Why would you recommend working at Experian?
First and foremost, for the amazing co-workers and atmosphere. I cherish the opportunity to work on exciting analytics projects with a team of people who are very dedicated, hard-working, innovative and fun.
This would also be an amazing place for you to work if you want to challenge yourself to explore unchartered territory in advanced analytics.
Data modelling
Build bespoke models to predict a person or customer segment’s propensity to buy, potential spend, likelihood of churn, risk potential or likelihood to pay.
Data engineering
In this more technical role, the focus is on gathering, preparing, processing and manipulating data to support data modelling.
Analytics consultancy
Working closely with clients to understand their requirements, you will feedback the insights and ideas that help us develop bespoke new analytics solutions.
Data science
Be heavily involved in research and development, with the freedom to come up with new ideas and access to our cutting-edge data processing facilities.
Analytics engineering
Use software programming to develop and implement analytic algorithms and data processing tools.
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