Role Description The Senior Catastrophe Modeler supports the integrity and effectiveness of catastrophe modeling processes and data within K2. This role is responsible for analyzing and assessing the potential impact of natural and man-made disasters on business operations, while partnering closely with underwriting teams to model individual accounts and develop import templates. The position also involves building and enhancing complex modeling systems, collaborating with cross-functional stakeholders, and delivering strategic insights to help mitigate, optimize, and manage risk across the organization. Key Responsibilities - Take responsibility for the processes which form the basis of exposure and modelling reporting within K2, including maintaining data integrity between warehousing, aggregate, cat modelling and reporting systems. - Maintain catastrophe models to evaluate the potential impact of natural and man-made disasters on our organization's assets, including property, infrastructure, and other relevant areas. - Analyze large datasets, historical data, and scientific research to assess the probability and severity of various catastrophic events, such as earthquakes, hurricanes, floods, and terrorism. - Collaborate with cross-functional teams, including actuaries, underwriters, and risk managers, to understand their requirements and incorporate them into the Exposure Management function. - Validate and calibrate catastrophe models using historical event data and industry benchmarks, ensuring accuracy and reliability. - Provide expertise and guidance on catastrophe risk assessment to senior management, assisting in the development of risk management strategies/policies and portfolio optimization. - Stay updated on the latest advancements in catastrophe modelling techniques, tools, and industry best practices, and recommend enhancements to existing models or implementation of new models as appropriate. - Prepare comprehensive reports, presentations, and visualizations to effectively communicate complex risk assessments and recommendations to stakeholders and external parties. Qualifications - Expertise in RMS and/or Verisk’s AIR catastrophe model vendor platform - Strong technical problem-solving skills with ability to interpret modelled results with business leaders - Excellent verbal and written communication skills - Self-motivated to work independently or in a team as needed; ability to prioritize workload Requirements - College degree in Computer Science, Mathematics, Finance/General Business, or Engineering or equivalent education and/or experience - 4+ years of catastrophic modeling and management reporting experience - Strong Excel, Access, PowerPoint, and SQL knowledge Benefits - Competitive pay - Bonus plan - Medical, dental, and vision insurance - Paid time-off in year of hire - 401(k) with employer match Salary Salary Range: 98,000-120,000 USD/Per year, depending on experience

• Take ownership of the design and execution of data science projects, ensuring high-impact analytics solutions. • Partner with client stakeholders to understand business challenges and develop data-driven strategies. • Oversee data acquisition and integration, ensuring data quality and reliability. • Apply and refine machine learning and predictive modeling techniques to solve complex business problems. • Guide the deployment and integration of predictive models into business applications. • Develop and implement strategies for optimizing model performance and monitoring over time. • Present findings and recommendations to executives, translating complex data concepts into actionable business strategies. • Mentor and support junior and senior team members in data science methodologies and best practices. • Influence data governance and best practices within the organization.

• Develop and maintain data quality monitoring frameworks, including defining key data quality metrics and thresholds • Build and maintain quality dashboards and reports using programming languages (e.g., SQL, Python) and BI tools to provide near real-time study insights • Oversee data validation, coding, reconciliation (e.g., safety, device, external vendor data), and risk-based review processes • Ensure compliance with ICH-GCP, 21 CFR Part 11, HIPAA, and applicable FDA expectations for regulated SaMD trials • Partner with Engineering and Data teams to support ingestion, transformation, and traceability of multi-source clinical datasets (e.g., wearable data, ePRO, device integrations, CRO exports) • Manage CRO and vendor data management deliverables, ensuring sponsor oversight and quality standards are met • Identify data-related risks early and drive mitigation strategies • Contribute to SOP development and help standardize scalable, repeatable data management practices across Research Operations

Role Description Data scientists at Thoughtworks are responsible for leading and executing data science projects. They employ their profound expertise in statistics, modeling, machine learning algorithms, and data mining methodologies to render business value and illuminate data-driven insights. - Lead and manage data science projects from inception to completion. - Collaborate with stakeholders to understand strategic objectives and identify opportunities to leverage data for AI and machine learning. - Responsible for overall AI system design, problem framing, and governance. - Design, develop, and implement data science strategies that drive measurable business results. - Design experiments to rapidly test ideas and assumptions. - Use quality metrics to select machine learning models for production. - Communicate technical findings and insights clearly to stakeholders. - Contribute to the growth of the data science community and promote data literacy. - Address ethical concerns and adhere to ethical guidelines using FATTER AI (fairness, accountability, transparency, trustworthiness, explainability, responsibility). - Work with CD4ML practices and data versioning tools. Qualifications - Experience in leading the analysis and modeling of different datasets. - Experience with statistical modeling, hypothesis testing, machine learning, deep learning, and optimization. - Specialty in at least one area of AI (e.g., NLP, computer vision, Generative AI). - Experience with R, Python, or equivalent statistical/data analysis tools. - Ability to gather and preprocess large volumes of structured and unstructured data. - Analyze datasets using statistical and visualization techniques. - Develop and implement machine learning models and predictive analytics. - Evaluate model performance using appropriate metrics. - Interpret and communicate findings to non-technical stakeholders. - Ensure compliance with data privacy regulations and ethical standards. Requirements - Understand the importance of stakeholder management and liaise effectively. - Resilient in ambiguous situations and adaptable to challenges. - Proactively manage risks and conflicts. - Eager to coach, mentor, and motivate others. - Advocate for technical excellence while being open to change. - Proven leader with a track record of encouraging professional development. - Strong relationship-building skills that create new opportunities. Benefits - Support for career development through interactive tools and numerous programs. - Empowerment in career journeys with a focus on continuous learning. Company Description Thoughtworks is a dynamic and inclusive community of bright and supportive colleagues who are revolutionizing tech. As a leading technology consultancy, we’re pushing boundaries through our purposeful and impactful work. - Over 30 years of delivering extraordinary impact with clients. - Helping clients solve complex business problems with technology as the differentiator.