Quantitative Risk Analyst, Credit Risk Data Management [Assistant/Regular/Senior]

Nordea; Finland; On-site; EUR 70,000 - 110,000; Full time

Benefits offered by this job

Hybrid working model

Job summary

Nordea in Finland seeks a Quantitative Risk Analyst to contribute to data analytics, optimize data flows, and support data governance across credit risk models. You will coordinate data activities and communicate effectively within Risk Models areas.

Key responsibilities include data quality root‑cause analysis, data reconciliation, and ensuring robust data lineage, with a focus on delivering accurate reports to senior management and external bodies.

Qualifications

• Experience with Credit Risk modeling, capital reporting and regulatory requirements such as BCBS239 and TRIM.
• Knowledge of SQL, SAS, Snowflake and Python or similar.
• Master’s degree in finance, economics, engineering, physics or mathematics.
• Strong focus on results, deliveries and deadlines.
• Experience with Big Data would be an asset.
• Interest in finance and technology.

Responsibilities

• Root‑cause analysis for data quality issues and data reconciliation across sources.
• Optimize data flows and algorithms to enhance data processes.
• Own and manage all data used in credit risk models across the end‑to‑end lifecycle.
• Identify and govern critical data elements with knowledge of credit risk models and regulatory expectations.
• Secure the Data Governance framework with robust Data Quality Controls and document Data Lineage.
• Prepare reports and documentation for senior management and external reporting.

Skills

Data analytics

Data governance

Communication

Analytical thinking

Attention to detail

Collaboration

Problem solving

Education

Master's degree in finance or related

Tools

SQL

SAS

Snowflake

Python

Job description

What you'll be doing

As a Quantitative Risk Analyst, the specific role may vary based on qualifications, but you could play a valuable role in data analytics, optimizing data flows, product management, or as a data governance specialist. Your role could also include coordinating data‑related activities and ensuring proper communication within the teams and across other Risk Models areas.

Main responsibilities in this role:

• Root‑cause analysis for data quality issues, where we meticulously investigate and identify the underlying reasons for any discrepancies in our data. This is closely followed by data reconciliation, ensuring that our data sets are consistent and accurate across different sources.
• We focus on optimizing data flows and algorithms to enhance the efficiency and effectiveness of our data processes.
• Own and manage all data used in credit risk models across the end‑to‑end lifecycle, applying a data product mindset to capture, enhance and realize value throughout credit risk models.
• Identify and govern critical data elements through strong knowledge of credit risk models, regulatory expectations and capital.
• Secure our Data Governance framework and processes with focus on effective Data Quality Controls, also ensuring documentation of Data Lineage toward all data providers and consumers for credit risk data.
• Preparing reports and other documentation for senior management and external reporting is also an integral part of our role, ensuring transparency and informed decision‑making.

Who you are

• Have an adaptability to thrive in fast‑paced and dynamic environments.
• Are structured and able to coordinate several deliveries simultaneously.
• Are self‑driven and able to work independently but also enjoy collaboration with others.
• Have strong analytical skills and keen attention to detail with the ability to analyse complex data and processes to derive meaningful insights.
• Have good communication and presentation skills, are not afraid to speak up and can effectively convey business requirements to IT teams and facilitate collaboration between stakeholders.
• Are curious and proactive, focus on solutions rather than problems and share our enthusiasm for developing and learning and constantly improving your skills and competences.

Background and skills

• Experience with Credit Risk modeling, capital reporting, and understanding regulatory requirements such as BCBS239 and TRIM.
• Knowledge of SQL, SAS, Snowflake, Python or similar.
• Master’s degree in finance, economics, engineering, physics, mathematics or similar.
• A strong focus on results, deliveries and deadlines.
• Experience with Big Data would be an asset.
• An interest in finance and technology.

What we offer

Hybrid working model – we believe in the value of bringing people together and at the same time we embrace the freedom of flexibility.