Risk and Resilience Engineer

We need to output HTML fragment with sections for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We need to parse the job posting. First, there is a line: "Your Team Responsibilities Risk & Resilience Modeler". That's weird. Probably the title is "Risk & Resilience Modeler". The posting includes sections: "Your Key Responsibilities What You’ll Do", then bullet list. Then "What We’re Looking For". Then "Your Skills And Experience That Will Help You Excel What You’ll Bring". Then "What Will Make You Stand Out". Then "About MSCI What we offer you". Then salary range etc. We need to map to headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to decide what content goes where. - About the role: likely the introductory paragraph(s) before responsibilities. The posting starts with "Your Team Responsibilities Risk & Resilience Modeler We are looking for an expert..." That's a bit garbled. Probably the "About the role" content: description of role, mission, etc. We'll extract the paragraph(s) before "Your Key Responsibilities". Let's locate. The text: "Your Team Responsibilities Risk & Resilience Modeler We are looking for an expert in risk and resilience of the built environment to help advance how physical climate risk is translated into real-world financial impacts. Our Science teams develop world-class hazard models across a range of natural perils. In this role, you will work closely with scientists, engineers, and data experts to build sophisticated loss and resilience models that quantify what those hazards mean for buildings and infrastructure around the world. You will develop models that translate exposure to hazards such as flood, wildfire, and wind into estimates of structural damage, repair costs, downtime, and broader economic impacts. These models are a critical link between physical and financial risk, enabling our customers to understand not only where risk exists, but what it could mean financially—and how investments in resilience and adaptation can reduce that risk. This is a highly interdisciplinary role at the intersection of engineering, resilience, materials science, cost estimation, statistics, and data science. We are particularly interested in candidates who are comfortable solving complex technical problems where data may be incomplete, inconsistent, or scarce, and who can combine first-principles reasoning with empirical evidence and modern quantitative methods to develop defensible, scalable solutions. https://careers.msci.com/life-at-msci" Then "Your Key Responsibilities What You’ll Do" then bullet list. Thus About the role = that paragraph(s) before responsibilities. Responsibilities = bullet list under "Your Key Responsibilities What You’ll Do". Need to extract each bullet. Let's extract bullet points: - Connect physical climate risk to financial risk by developing custom loss models that quantify impacts to buildings, infrastructure, and other assets globally, integrating them with First Street’s hazard models. - Model damage, recovery, and economic impacts by developing estimates of structural damage, repair costs and timelines, downtime, and indirect impacts using approaches including engineering first principles, cost estimation, statistical methods, and machine learning. - Turn imperfect data into actionable models by analyzing historical loss and observational datasets, identifying data limitations and quality-control issues, and developing technically sound approaches to address them. - Validate model performance and quantify uncertainty through statistical analysis of model predictions, observational data, sensitivities, and uncertainty to ensure outputs are scientifically rigorous and decision-useful. - Translate research into scalable modeling approaches by evaluating academic literature, engineering research, industry standards, and emerging methodologies and incorporating relevant insights into quantitative loss and resilience models. - Characterize the global built environment by analyzing building codes, exposure datasets, construction practices, materials, occupancy types, and regional differences to inform vulnerability and loss model development across diverse geographies. - Model the value of resilience and adaptation by developing property-level adaptation scenarios that allow customers to understand how protective measures can reduce damage and downtime and evaluate the potential return on investment of resilience interventions. Now "What We’re Looking For" likely maps to Requirements or Qualifications. The posting says: "The ideal candidate brings expertise across several disciplines rather than fitting neatly into a single technical category. Your background may include structural or civil engineering, resilience engineering, materials science, catastrophe or risk modeling, construction cost estimation, statistics, or data science. You are comfortable moving between engineering fundamentals and large datasets, challenging assumptions, working through uncertainty, and developing practical solutions when perfect data does not exist. Most importantly, you are excited by the opportunity to build models that transform complex climate science into information that can support better financial, infrastructure, and resilience decisions. This is an opportunity to work on technically challenging problems with meaningful real-world impact—helping define how climate-driven physical risk, financial consequences, and the value of resilience are understood at the property level and at global scale." That could be Requirements or Qualifications. We'll treat as Requirements (maybe also Qualifications). Then "Your Skills And Experience That Will Help You Excel What You’ll Bring" is Skills section. Then "What Will Make You Stand Out" could be additional Skills or Qualifications. We'll combine into Skills. Then "About MSCI What we offer you" includes Benefits, Pay, etc. Salary range: $102,000 - $133,000 / year. Plus eligible for annual bonus. Transparent compensation schemes and comprehensive employee benefits, tailored to your location, ensuring your financial security, health, and overall wellbeing. Flexible working arrangements, advanced technology, and collaborative workspaces. A culture of high performance and innovation... Global Orientation program... Learning@MSCI platform, AI Learning Center, LinkedIn Learning Pro and tailored learning opportunities... Multi-directional career paths... Employee Resource Groups list... etc. Thus Benefits: list of benefits (flexible working, technology, workspaces, culture, learning programs, career paths, ERGs). Pay: salary range and bonus. Schedule: maybe flexible working arrangements? Could be schedule. But we have flexible working arrangements under benefits; schedule maybe not explicitly given. Could omit Schedule if not specific. We need to avoid placeholder text like "commensurate with experience". Not present. We must not repeat job title as heading. Not include Job ID etc. We need to output only HTML fragment, no /. Use

for section headings. Use

• for lists. Use

  for prose. We need to decide which sections to include: About the role, Responsibilities, Requirements, Skills, Benefits, Pay. Possibly Qualifications not needed if covered by Requirements. But we could include Qualifications if there is distinct content. The "What We’re Looking For" could be Requirements. The "Your Skills And Experience..." could be Skills. The "What Will Make You Stand Out" could be additional Skills or Qualifications. We'll treat as Skills. Thus sections: - About the role (intro paragraph) - Responsibilities (list) - Requirements (the "What We’re Looking For" paragraph) - Skills (combined "Your Skills And Experience..." and "What Will Make You Stand Out") - Benefits (list of benefits from About MSCI) - Pay (salary range and bonus) We should not include Schedule as no explicit schedule. Now we need to preserve all substantive information, not invent or summarize away detail. Must not omit details. We need to convert paragraphs into

  . For lists, each bullet becomes

• . We need to ensure we don't include boilerplate like EEO, legal, scam warning, etc. Remove those. Now let's craft HTML. First, About the role: combine the paragraph(s) before responsibilities. It includes a URL? It includes "https://careers.msci.com/life-at-msci". That's a link; we should preserve as is? Probably keep as plain text; we could wrap in but not required. The instruction: preserve ALL substantive information; do not invent or summarize away detail. So we should keep the URL as plain text. It's okay. Thus About the role

  containing that paragraph. Now Responsibilities

  with each bullet. Now Requirements

  containing the "What We’re Looking For" paragraph. Now Skills: need to combine two parts. First part: "Your Skills And Experience That Will Help You Excel What You’ll Bring" then list of bullet-like sentences? Actually it's a paragraph with many items separated by periods. Let's extract that section: "Ph.D. preferred, or a Master’s degree with 3 - 5+ years of relevant experience in structural engineering, civil engineering, operations research, resilience engineering, catastrophe risk, or a related quantitative field.Structural Degree or Civil Engineering (with a structural focus).Strong technical foundation in vulnerability and loss modeling, statistics, probabilistic methods, and quantitative analysis, with the ability to translate complex physical processes into robust analytical models.Hands-on experience developing risk, vulnerability, or loss models for buildings and infrastructure, using engineering-based approaches, statistical methods, machine learning, or a combination of these techniques.Demonstrated ability to develop loss models from the ground up, from defining the underlying methodology and sourcing appropriate data through calibration, validation, uncertainty quantification, and implementation.Experience working with multi-hazard and catastrophe risk data, including hazard intensity measures, building-level damage and loss observations, exposure datasets, construction characteristics, and repair or construction cost data.Experience developing scalable and generalizable catastrophe risk models that can be applied across large portfolios, diverse asset types, and multiple geographic regions.Advanced proficiency in Python or comparable scientific programming languages, with experience developing reliable, maintainable, and reproducible analytical workflows.A rigorous, science-driven approach to model development, with a strong emphasis on accuracy, reliability, transparency, validation, and reproducibility.Strong understanding of the current research landscape in resilience, vulnerability, catastrophe risk, and loss modeling, including relevant engineering standards, technical guidelines, and emerging methodologies.Experience applying machine learning and AI techniques to engineering, risk, resilience, or other scientific modeling problems.Experience analyzing large and complex datasets in high-performance computing environments, either on-premises or using cloud platforms such as AWS, GCP, or Azure.Proficiency with collaborative software development practices and version control systems such as Git.A strong record of scientific research and publication, demonstrating the ability to conduct rigorous technical work and communicate complex methodologies and findings clearly." Note there are no spaces after periods; but we can keep as is. Second part: "What Will Make You Stand Out We are especially interested in candidates who combine deep technical expertise with the ability to operate in areas where established datasets or methodologies may not yet exist. You know how to move from first principles to a working model, make thoughtful assumptions when evidence is limited, test those assumptions against available data, and communicate uncertainty clearly. Experience building property-level loss models from scratch, working across multiple natural hazards, or developing models that connect physical damage and recovery to financial outcomes will be particularly valuable." We'll combine both into a single

  maybe? But they are not bullet list originally; they are sentences. Could treat as

  paragraphs. However instruction: Use

  • for any list of duties/requirements/benefits. For skills, it's not a list but a paragraph of items. Could still use

    . But we could also split into

    if we treat each sentence as item. However the instruction says use
    • for any list of duties/requirements/benefits. Skills is not explicitly a list; but we could still use

      . Safer to use

      for skills section. Thus Skills

      containing both paragraphs combined (maybe separated by a space). Now Benefits: need to extract from "About MSCI What we offer you". Let's pull that paragraph: "Salary range: $102,000 - $133,000 / year.Plus eligible for annual bonus.Transparent compensation schemes and comprehensive employee benefits, tailored to your location, ensuring your financial security, health, and overall wellbeing.Flexible working arrangements, advanced technology, and collaborative workspaces.A culture of high performance and innovation where we experiment with new ideas and take responsibility for achieving results.A global network of talented colleagues, who inspire, support, and share their expertise to innovate and deliver for our clients.Global Orientation program to kickstart your journey, followed by access to our Learning@MSCI platform, AI Learning Center , LinkedIn Learning Pro and tailored learning opportunities for ongoing