Role Description As a Senior Data Scientist at Coalition you will be responsible for measuring, understanding, and helping optimize Coalition’s underwriting. You will perform statistical analysis to provide data-driven insights. You will help us understand and improve our cyber risk selection and reduction, pricing and automation in order to grow our revenue in a safe and efficient manner. - Analyze diverse datasets including claims data, cybersecurity risk signals, and underwriting databases to extract meaningful patterns and insights. - Large scale data analysis with the objective of producing valuable risk signals to be used for underwriting or risk evaluation of organizations. - Develop and refine statistical and machine learning models to assess cybersecurity risks with applications to underwriting and pricing. - Create comprehensive reports on underwriting efficiency metrics and risk selection quality to inform strategic decisions. - Apply statistical techniques to evaluate and improve our cyber risk assessment methodology. - Provide analytical support for underwriting strategies to balance growth with risk management. - Identify, analyze, and implement opportunities to automate underwriting workflows using advanced analytics and data-driven strategies. - Collaborate cross-functionally with actuarial, product, and engineering teams to implement data-driven improvements. Lead cross-functional initiatives in area of expertise. - Serve as both a technical lead and a mentor within the underwriting team. - Work alongside other data scientists, software engineers, and cyber security engineers to improve underwriting at Coalition. Intellectual curiosity and proactive approach to identifying improvement opportunities. Qualifications - Bachelor's degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Actuarial Science, or related discipline). - 5+ years of experience in underwriting, quantitative analysis, or risk modeling in the insurance industry. - Knowledge of underwriting, pricing, reserving, or risk management processes in insurance. - Advanced SQL skills for querying complex databases and joining disparate data sources. - Expertise in data manipulation and analysis using Python, R, or similar analytical tools. - Experience with data visualization tools (e.g., Tableau, Power BI, Looker). - Experience with dashboard creation for operational metrics tracking. - Strong communication and analytical skills. - Capable of working with remote teams. Requirements - Actuarial qualification (nice-to-have). - Experience in cyber insurance or cyber security (nice-to-have). - Prior experience or willingness to learn how to work with large datasets and big data technologies (Snowflake, AWS Athena) (nice-to-have). Benefits - 100% medical coverage, including outpatient care. - Life insurance. - 25+ paid holidays. - Annual home office stipend. - 7% employer pension contribution. - Mental and physical health wellness programs like Headspace, Wellhub. - Competitive compensation and opportunity for advancement.

• Develop, maintain and enhance ETL/ELT processes for data integration and transformation. • Build, test, troubleshoot and migrate data workflows, mappings and jobs. • Implement and sustain Information Governance processes. • Work on initiatives related to data quality, cataloging, metadata, master data management (MDM), data privacy and data security. • Ensure the reliability, integrity and availability of corporate information.

• Own high-impact data science work across product data science and fair play • Create and build novel algorithms, models, and data-powered features that directly shape the chess experience for our users • Partner across the company on product vision and execution • Work closely with product managers, engineers, designers, and writers • Design and deploy creative heuristics, algorithms, and models that identify cheating at scale • Raise the quality and sophistication of our approaches over time • Manage a lean team of data scientists • Turn strategy into clear team objectives and results • Help data scientists grow into scientists who can operate with more speed and independence over time • Communicate early and often

• Responsible for refactoring the Optimization algorithm written in Python using Object Oriented Programming • Work on the latest applications of data science to solve business problems in the Supply chain and optimization space of Retail and/or CPG. • Utilize advanced statistical techniques and data science algorithms to analyze large datasets and derive actionable insights related to Pricing Optimization. • Develop and implement predictive models and optimization algorithms to improve inventory management, reduce stockouts, and optimize resource allocation across the supply chain. • Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions. • Design and execute experiments to evaluate the effectiveness of different replenishment strategies and allocation policies. • Monitor and analyze key performance indicators (KPIs) related to replenishment and supply chain allocation, and provide recommendations for continuous improvement. • Stay abreast of industry trends and best practices in data science, replenishment optimization, and supply chain management, and leverage this knowledge to drive innovation within the organization. • Collaborate, coach, and learn with a growing team of experienced Data Scientists.