Must have

• SAS

• Python

• PySpark

• SQL

• Hadoop

• Business analysis

• Communication skills

• English

Requirements description

REQUIREMENTS:

• Solid professional experience in data analysis, ideally within financial services or risk analytics.
• Proficiency in tools such as SAS, Python, PySpark, SQL, or Hadoop; familiarity with Prophecy is a plus.
• Strong analytical thinking, organizational ability, and familiarity with data architecture and business analysis practices.
• Comfortable working under time constraints and managing multiple concurrent priorities.
• Knowledge of risk data, regulatory reporting, or banking risk systems is highly preferred.
• Excellent interpersonal and communication skills; proven ability to collaborate within global and cross-functional teams.

Offer description

Join one of the world’s largest and most respected financial institutions, serving millions of customers across global markets. With a strong presence in both established and emerging economies, the organization is committed to innovation, responsible finance, and driving sustainable growth through advanced technology and data-driven strategies.

What is Antal?

Recruitment company!

We are the leader in the recruitment of specialists and managers, as well as in HR consulting. The brand is present in 35 countries and has been operating in Poland since 1996. During this time we built many candidates' careers, thanks to our flexible and comprehensive approach to all recruitment processes.  Our specialists, completely free of charge, will help you find and get the best job for you!

What will you gain by applying for Antal job offer?

Free career support!

By applying for Antal offers, you will receive support from our Consultant, who will keep in touch with you via e-mail or phone, help you prepare for the interview, and take care of the quality of the recruitment process.

Your responsibilities

1. Support complex data analytics initiatives related to credit risk model development and monitoring.
2. Handle the ingestion, validation, and quality assurance of datasets from diverse internal and external sources.
3. Build and maintain ETL pipelines with attention to data lineage, traceability, and integrity.
4. Collaborate with international teams across data, risk, and IT on both operational and strategic change initiatives.
5. Translate business and model-related data requirements into structured, actionable data assets, contributing to ongoing process optimization.