This is a profile from the 2022 version of the DataIQ 100.
The latest list is available here.
Natalia Lyarskaya, chief data officer, ZestMoney
What has been your path to power?
I started my career as a statistics analyst in 2006 in CRIF, at that time an Italian credit bureau and credit risk consultancy company which was just about to open an office in Moscow. I spent the first months in Italy in the company’s HQ, getting trained on the new SAS softwareand learning the basics of scorecard development for the financial sector. I then decided to pursue my studies and do a PhD in Economics at the Sorbonne University in Paris. After completion in 2011, I moved to London and joined fintech start-up Wonga as its first data scientist building risk and fraud algorithms. There I had an opportunity to lead all of its data and ML initiatives to evaluate credit risk, prevent fraudulent behavior, optimise product and collection strategies, as well as to develop rigorous ID verification products for the UK, as well as a number of other highly-regulated international markets.
As the company was growing fast, I also grew my team and became lead data scientist, overlooking UK and International markets from a data and modelling perspective. Later, in 2014, I created a new team focusing on alternative data sources and emerging ML technologies for risk and fraud assessment. In August 2015, I joined ZestMoney, one of the largest and fastest-growing consumer lending fintech companies in India, with the mission to set-up its data science team in India, as well as to build its fully-automated decision engine using AI/ML technologies.
Since 2018, I have held the role of chief data officer role at ZestMoney, where I have built data, AI and risk strategy functions from scratch, while creating an efficient AI operating model, building an AI center of excellence and establishing a data-driven culture within the company. I also got deep experience working closely with the technology team to create the proper design of data and decisioning systems, satisfying the company’s requirements, including data protection and AI ethics angles.
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