Physical Climate Risk Model Developer, Vice President
Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Oct 9, 2026. Citi scores A on the Alion truth index.
Citi’s Risk Management organization oversees risk-taking activities and assesses risks and issues independently of the front-line units. We establish and maintain the enterprise risk management framework that ensures the ability to consistently identify, measure, monitor, control and report material aggregate risks.
We’re currently looking for a high caliber professional to join our team as Risk Reporting Senior Manager, Vice President (Internal Job Title): Risk Reporting Senior Manager, Vice President- C13 based in Mumbai, India. Being part of our team means that we’ll provide you with the resources to meet your unique needs, empower you to make healthy decisions and manage your financial well-being to help plan for your future. For instance:
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The Physical Risk Model Developer will be part of the Climate Risk Analytics team within Credit, Climate and Obligor Risk Analytics (CORA) in the Data, Analytics, Reporting, and Technology (DART) organization. This role develops quantitative models and methodologies to assess the impact of physical climate and nature-related risks across Citi's portfolios and operations. The role requires strong domain expertise of climate/catastrophe modeling and regulatory policies, leveraging quantitative modeling, geospatial analytics, and data science to support risk identification, scenario analysis, stress testing, and risk management across a multidisciplinary environment.
In this role, you’re expected to :
- Develop and implement quantitative models assessing physical climate and nature-related risks, including hazard, exposure, vulnerability, and financial/credit impacts across portfolios, sectors, and geographies.
- Build geospatial analytical pipelines to evaluate acute and chronic physical hazards using complex climate, environmental, and asset-level datasets.
- Translate scientific, environmental, and physical risk drivers into financial metrics for stress testing, scenario analysis, and portfolio analytics.
- Leverage big data and machine learning techniques to solve complex data science challenges and deliver deployable analytical solutions.
- Evaluate and integrate external climate, hazard, geospatial, and nature-related datasets/models with internal risk and portfolio data.
- Partner with external vendors and internal First Line (1LOD) and Second Line of Defense (2LOD) on the sourcing of hazard, exposure, and vulnerability data, and on the design of climate risk assessment features.
- Write production-grade analytical code and support model implementation in controlled technology environments.
- Perform model testing, sensitivity analysis, benchmarking, and quantitative assessments to evaluate model performance and limitations.
- Author technical documentation for model governance, validation (MRM), and regulatory requirements.
- Collaborate across Risk, Technology, Model Risk Management, and business sponsors, presenting analytical findings and model performance clearly to both technical and non-technical audiences.
As a successful candidate, you’d ideally have the following skills and exposure:
- 6-10+ years of relevant experience in quantitative modeling, data science, climate risk, catastrophe (CAT) modeling, or environmental risk analytics.
- Advanced degree (MS or PhD) in a quantitative discipline: Hydrology/Meteorology, Climate Science, Environmental or Life Sciences, Statistics, Physics, Engineering, Mathematics, or other natural hazard related disciplines is required.
- In-depth knowledge of industry and academic climate and CAT modeling methodologies, vendor/public weather and hazard models, and climate data sources.
- Proven expertise in physical climate risk, natural hazard modeling, nature risk, or geospatial analytics.
- Professional experience in statistical modeling, Bayesian inference, spatial statistics, or machine learning methodologies.
- Expertise in programming, data modeling, and data management, with strong proficiency in Python, SQL, and Unix/Linux environments.
- Strong technical documentation skills with proven experience preparing quantitative methodologies for model validation and governance.
- Excellent communication and presentation skills, with demonstrated ability to translate complex model design, assumptions, and performance metrics to both technical and non-technical stakeholders.
Education:
- Advanced degree (MS or PhD) in a quantitative discipline: Hydrology/Meteorology, Climate Science, Environmental or Life Sciences, Statistics, Physics, Engineering, Mathematics, or other natural hazard related disciplines is required.
Bachelor's/University degree, master’s degree preferred
Working at Citi is far more than just a job. A career with us means joining a family of more than 230,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.
Take the next step in your career, apply for this role at Citi today
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Job Family Group:
Risk Management------------------------------------------------------
Job Family:
Model Development and Analytics------------------------------------------------------
Time Type:
Full time------------------------------------------------------
Most Relevant Skills
Analytical Thinking, Credible Challenge, Data Analysis, Governance, Policy, Procedure, and Regulation, Risk Management Lifecycle.------------------------------------------------------
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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