Job Description

About the Role

As a member of the PAE team you will be part of the Swiss Re Insurance-Linked Investment Advisors Corporation ("SRILIAC") in NYC, an investment advisor fully owned by Swiss Re with focus on catastrophe bonds.  This position works directly with the PAE and SRILIAC team and across other functions including underwriting, cat perils, legal, finance, risk and others both internally and externally.

In this role you will design and deploy advanced data models, visualizations, and foundational datasets that support strategic decision-making across multiple SRILIAC verticals, enabling data-driven insights at every stage of the investment lifecycle.  The role requires a commitment to continuous learning and upskilling to meet evolving needs and goals.

Additional responsibilities include :

• Optimize and streamline data pipelines, dashboards, frameworks, and systems accelerating development and scalability of data assets across the portfolio, improving efficiency and accessibility.
• Close collaboration with teams in investigating investment strategies, enhancing predictive models, interpretation of market signals and the testing of innovative ideas.
• Regular portfolio risk modeling and analysis, providing actionable insights that align with current strategies.
• Monitoring natural catastrophe model updates, engaging with our Cat Perils team to ensure risk assessments reflect the latest risk profiles.
• Build and maintain dynamic dashboards, tailored reports, scalable data quality audits and robust alerting and anomaly detection systems, identifying and addressing inconsistencies.
• Ensure system reliability across data pipelines and orchestration frameworks by using best practices in change management, CI/CD, and configuration-as-code principles.

About the Team

The SRILIAC Portfolio Management team's mandate is to manage the ILS strategies under management by SRILIAC and to generate management fees for Swiss Re through third-party capital.  PAE is responsible for design, implementation, and deployment of analytical solutions that facilitate SRILIAC Portfolio Managers in risk modeling/monitoring, portfolio construction/monitoring, scenario analysis, exposure monitoring, portfolio optimization, forecasting, and reporting.

About You

Adaptive and comfortable in a global, multicultural team environment, bringing a collaborative mindset and an appreciation for diverse perspectives in achieving project objectives.  You have a successful track record of identifying and implementing performance improvements for ETL processes and dashboards, optimizing for both cost and efficiency.  Skilled in communication and stakeholder engagement, you work effectively on projects with evolving objectives and requirements!

Additional requirements include :

• Bachelor's degree in Computer Science, Math, Physics, or other technical fields

• Experienced in version control systems (e.g. Git) and deployment/CI tools, ensuring seamless integration, deployment, and continuous improvement across development cycles.
• Strong foundation in statistics and machine learning, with familiarity in key algorithms, frameworks, and techniques applicable to risk modeling and data-driven insights.
• Solid understanding of data warehousing principles and hands-on experience with relational databases, particularly PostgreSQL, to support efficient data storage and retrieval.
• Proficient with Azure cloud services and with business intelligence tools like Power BI, to create impactful data visualizations and facilitate strategic decision-making.
• Competent with MS Excel, PowerPoint, and Word, with experience creating clear, actionable presentations and reports for diverse audiences.

Experience required :

• 1 + years of working experience in Insurance Linked Securities, Reinsurance, or natural catastrophe modeling, with a strong understanding of industry-specific data and risk factors.
• 2+ years of practical experience with Palantir Foundry, including expertise in developing, optimizing, and deploying data solutions within the platform.
• 2 + year of experience building and maintaining reliable data pipelines in production environments, demonstrating a solid understanding of data engineering best practices.
• 2 + years of experience in designing, developing, and managing robust data models from both structured and unstructured data sources to support complex analytical needs.
• 3 + years of experience with SQL, ETL processes, data modeling, and development in programming languages such as Python, PySpark, or Scala, with a track record of building scalable data solutions.

For New York City the estimated base salary range for this position is $112,000 to $168,000. The specific salary offered for this or any given role will take into account a number of factors including but not limited to job location, scope of role, qualifications, complexity/specialization/scarcity of talent, experience, education, and employer budget. At Swiss Re, we take a "total compensation approach" when making compensation decisions. This means that we consider all components of compensation in their totality (such as base pay, short-and long-term incentives, and benefits offered), in setting individual compensation.

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