Do you have what it takes to join Channel VAS, the global Fin Tech leader?
Channel VAS lends more than $4.5 million USD to over 550 million people in 25 countries worldwide - and these numbers keep growing every day! We employ only the best to join our team of highly skilled professionals in our Operations Center in Greece and other countries.
Credit Risk Data Scientists are significant contributors of Channel VAS' data driven automated decision making, risk management and profits optimization.
They have extensive experience with credit and profit scoring, the development and deployment of advanced algorithms, and the day-
to-day risk management of large portfolio of loans. They have the capability (i) to perform advanced risk analytics, (ii) design and develop statistical and machine learning algorithms for credit issuance and risk management, and (iii) operationalize them in the daily risk management activities of large portfolios with the aim to optimize profits.
Credit Risk Data Scientists are part of a large team of 10 people, working closely with Big Data Engineers and Analysts.
Manage large portfolios of micro-loans with the use of advanced algorithms and analytics to optimize profits.
Develop and deploy advanced credit risk models and algorithms.
Design, develop and implement scorecards for nano- and micro-finance.
Analyze large data volumes to identify credit risk factors.
Develop strategies for credit risk management and revenue maximization
Transfer knowledge on credit risk model development and management.
Required Experience & Qualifications :
BSc and MSc in Mathematical Sciences, Computer Science or Finance from an accredited institution.
Minimum of 3 years’ experience in a related role (e.g. credit risk analyst / manager and / or data scientist).
Strong analytical skills, evidence of statistical / machine learning models and algorithms development.
Hands-on experience at least in two of the following (with descending significance) : Credit risk model development and deployment Credit risk management Risk analytics Profits Optimization Machine learning
Ability to set-up, organize and monitor pilots for testing and comparing risk models
Experience in and ability to gain risk insights analyzing large volumes of data.
Additional requirements (will be considered a plus) :
PhD in Mathematical Sciences, Computer Science or Finance from an accredited institution.
Hands-on experience on big data processing and analytics.
Key competencies :
Passion for learning new technologies and eagerness to collaborate with other creative minds
Strong desire for exploring, evaluating and understanding new technologies
Ability to hit tight deadlines and work under pressure and strict attention to detail
Excellent judgment, organizational and problem-solving skills
Strong interpersonal and communication skills
Competitive salary and benefit package
Comprehensive private healthcare insurance
Company phone and laptop