About the Role
Andersen is hiring a Big Data Scientist in Tashkent for a project developing an automated lending platform with ML-based credit scoring, predictive analytics, and improved credit risk assessment. Our customer is a large international technology organization operating in the digital infrastructure domain. It develops and maintains high-load platforms that process and manage significant volumes of data across multiple regions.
Responsibilities
•Developing credit scoring and predictive analytics models for corporate borrowers.
Requirements
•Experience as a Data Scientist for 5+ years.
•Experience working with banking products and in the fintech industry.
•Hands-on experience with Python and PySpark.
•Experience developing credit scoring models (application and behavioral scoring) and Probability of Default (PD) models.
•Understanding of PD, LGD, and EAD metrics and their application in Expected Credit Loss (ECL) calculations under IFRS 9.
•Experience working with large-scale datasets.
•Strong SQL skills.
•Experience in model validation, including Gini, KS, PSI, and backtesting.
•Level of English – from Intermediate+ and above.
Nice to Have
•Experience with corporate credit scoring, financial statements, and external data sources (credit bureaus and tax authorities).
Conditions
•The opportunity to change the project and/or develop expertise in an interesting business domain.
•Guarantee of professional, financial, and career growth!
•The company has introduced systems of mentoring and adaptation for each new employee.
•The opportunity to earn up to an additional 1,000 USD per month, depending on the level of expertise, which will be included in the annual bonus, by participating in the company's activities.
•Access to the corporate training portal, where the entire knowledge base of the company is collected and which is constantly updated.
•Bright corporate life (parties / pizza days / PlayStation / fruits / coffee / snacks / movies).
•Certification compensation (AWS, PMP, etc).
•Referral program.
•Private health insurance and compensation for sports activities.
