10+ years of hands-on experience in
Python programming
with strong expertise in
data manipulation, analysis, and transformation using SQL
Extensive experience working in the
Banking domain
, particularly within
Risk Management functions
Proven experience in developing, enhancing, and supporting
Risk Models
including
Credit Risk, Market Risk, Liquidity Risk, and Operational Risk
Strong exposure to
risk modeling concepts
such as PD, LGD, EAD, stress testing, scenario analysis, and regulatory-driven models
Experience working with
Liquidity Risk frameworks
, balance sheet analytics, and regulatory metrics (LCR, NSFR)
Solid understanding and application of
data modeling and data model design techniques
for large-scale financial and risk datasets
Experience in handling
banking data sources
, regulatory datasets, and complex financial data structures
Ability to apply
Python-based analytical models
integrated with SQL-driven data platforms
Strong skills in
data validation, reconciliation, and quality checks
for risk and regulatory reporting
Experience working in
Agile environments
, collaborating with risk, data, and technology stakeholders
Strong understanding of
risk governance, controls, and regulatory compliance
within banking institutions