Informacje o stanowisku

Risk & Controls Senior Data Analyst – In-Business Quality Assurance WCR

Institutional Credit Managements (ICM) objective is to provide an integrated end-to-end credit underwriting, identification, measurement, management, monitoring and reporting for wholesale credit businesses across the enterprise. The ICM In-Business Quality Assurance function (QA) verifies that established standards and processes are followed and consistently applied. ICM Management uses the results of the quality assurance reviews to assess the quality of the groups policies, procedures, programs, and practices as relates to the management of wholesale credit risk. The results help management identify operational weaknesses, risks associated with the function, training needs, and process deficiencies.

We are currently looking for an IBQA high-caliber professional to join our team as Vice President, Risk & Controls Senior Data Analyst – In-Business Quality Assurance WCR based in Warsaw, Poland. Data analysis in this area involves extracting, transforming, and analyzing data to identify risks, assess controls, and improve their robustness by implementing automated solutions. They also contribute to the development of data-driven insights and reports. This role would suit an individual with both strong technical and business acumen in the Risk and Controls space.

This role reports to the ICM Head of In-Business Quality Assurance and Head of Data Analytics.

Key responsibilities

• Support the In-Business Quality Assurance Head of Data Analytics to set the global strategy for and lead the implementation and ongoing delivery of a robust data analytics and testing program for the Quality Assurance function as it relates to Wholesale Credit Risk (WCR) data governance.
• Provide effective challenge on the design and operation of the data and credit processes within ICM and report any identified gaps and concerns through quarterly reports to ICG senior management.
• Ability to query and clean complex datasets from multiple sources, to funnel into advanced statistical analysis.
• Hands-on experience designing, planning, prototyping, productionizing, deploying, maintaining, and documenting reliable and scalable data science solutions; deriving concrete insight from data and quantifying business impact.
• Develop processes and tools to monitor and analyse model performance and data accuracy.
• Collaborate with IBQA teams and QA Directors and provide them with analytics insights.
• Provide oversight and guidance over the assessment of complex data-related issues, structure potential solutions and drive effective resolution with stakeholders.

Qualifications and required experience

• Analytics and Business: Demonstrable experience of at least 6 years of data analytics, in innovation, modelling and analytics, internal audit, or similar functions at an investment or large commercial bank.
• Good grasp of Wholesale Credit Risk and Counterparty Credit Risk Processes and organizational awareness, to evaluate findings identified through the QA process, determine materiality, and partner with business to drive sustainable remediation.
• Excellent communication skills with the ability to collaborate with stakeholders at all levels to elicit requirements and priorities.

Competencies

• A logical and methodical mindset, strong analytical and problem-solving skills, with the ability to think critically, and work with others to propose creative solutions.
• Leadership in delivering complex or judgmental QA work, including identifying issues, analyzing multiple data points to draw informed conclusions and communicating them to senior stakeholders.
• Strong interpersonal communication skills for internal and external partners.
• Experience in analysing datasets and distilling actionable information and building end-to-end analytical process flows.
• Understanding of process redesign / re-engineering and execution.

Technical

• Strong skills in data analysis tools and programming languages (SQL, Python, R, Power BI, etc.). Python is essential.
• Creating clear and concise reports and visualizations to communicate findings to stakeholders.
• Analytical and problem-solving: ability to identify patterns, trends, and anomalies in data.
• Experience working with large datasets.

Qualifications

• Bachelor’s or Master’s degree in Maths, Computer Science, Statistics, Informatics, Information Systems, or another quantitative field.
• Data Analysis: SQL; Python; SAS; R; Alteryx; Splunk.
• Visualization: Tableau; QlikView; MS Power BI.
• Programming languages: Python, Java, C++.
• Experience with big data tools: Hadoop, Spark, Kafka, etc.

What we offer

By joining Citi Solutions Center Poland, you will be part of a business casual workplace with a hybrid working model (up to 2 days working from home per week), and receive a competitive base salary (annually reviewed) plus a range of benefits:

• Private Medical Care Program
• Life Insurance Program
• Pension Plan contribution (PPE Program)
• Employee Assistance Program
• Paid Parental Leave Program (maternity and paternity leave)
• Sport Card
• Holidays Allowance
• Sport and team recreation activities
• Special offers and discounts for employees
• Access to learning and development resources
• A discretionary annual performance-related bonus
• A chance to participate in affinity networks and charity initiatives

Alongside these benefits, Citi is committed to ensuring our workplace is inclusive and welcoming for everyone. We want the best talent to join, stay, and thrive.

Sounds like Citi has everything you need? Then apply to discover the true extent of your capabilities.

Note: Citi is an equal opportunity employer; qualified candidates will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our tools, Accessibility at Citi is available. View Citi’s EEO Policy Statement and Know Your Rights poster.

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