- Details
- Highlights
- Company
Job description
- Analyze data to identify trends, validate hypotheses, and deliver actionable insights to stakeholders.
- Troubleshoot data queries and ensure data quality and integrity.
- Develop, maintain, and optimize automated reporting scripts and resolve issues in automation workflows.
- Assist in ETL processes, contributing to data extraction, transformation, and loading tasks.
- Support the development and upkeep of data pipelines.
- Analyze credit risk and assist in the development and validation of risk models to ensure accuracy and reliability.
Requirements
- Proven experience as a Data Analyst.
- Strong Python (or R), SQL, and Excel skills.
- Data visualization experience.
- Analytical, detail-oriented, and problem-solving abilities.
- Team player with effective communication skills.
Bonus Skills:
- Financial services industry background.
- Knowledge of credit risk modeling and regulatory requirements.
- Degree in Statistics, Mathematics, Data Science, or related field.
Company offers
- Private health insurance.
- Flexible hybrid work environment.
- Access to vast, diverse datasets.
- Professional growth in a collaborative environment.
Location
- Vilnius, Vilniaus apskritis, Lithuania
Time of work
- Full-time
Elzė Laužikaitė
+37066031612
Alliance for Recruitment is the largest recruitment consultancy in the Baltics measured by capacity, number of successful placements and annual growth. We are a high performing team of recruitment experts from various different industries.
Our Client - SCORIFY is a rapidly growing company leveraging cutting-edge technologies in big data analytics, artificial intelligence, and machine learning. The company provides advanced data solutions to financial institutions, peer-to-peer lending platforms, telecoms, and central banks. SCORIFYs team of analysts and data experts focuses on developing products that offer insights through credit risk analysis, data integration, and comprehensive credit reports.
Their services include gathering and processing data from various sources, integrating with key systems like the Bank of Lithuanias risk database, and developing AI-driven models to assess creditworthiness and financial risks.