• Lead advanced analytics initiatives: Design experiments, develop statistical and machine learning models, and leverage AI to uncover trends, anomalies, and drivers of performance. • Take ambiguous business challenges and structure them into data-driven solutions. • Transform insights into action: Create clear narratives and recommendations supported by hypothesis testing and statistical analysis. • Communicate effectively: Present methodologies, insights, and recommendations to technical and non-technical audiences through compelling visualizations and storytelling. • Collaborate cross-functionally: Partner with data engineers, analysts, and business stakeholders to deliver end-to-end analytics solutions, dashboards, and reports using SQL, Python, R, and other tools. • Innovate and mentor: Contribute to the growth of Allstate’s Data Science practice by researching new tools, sharing best practices, and mentoring team members.

• Identify and drive high-impact ML/AI initiatives that advance Bitsight’s broader ML/AI strategy and long-term technical roadmap • Design, build, and deploy production-grade ML models and automation systems that support critical business features • Develop and maintain end-to-end ML pipelines, including data extraction, feature engineering, training, evaluation, deployment, monitoring, and automated feedback and retraining loops • Architect scalable ML/AI components that improve performance and reliability across cloud-based distributed systems • Analyze large-scale cybersecurity datasets to identify opportunities for improved classification, detection, and automation • Translate ML/AI outcomes into actionable product decisions and collaborate closely with other Stakeholders internally and externally • Establish and promote best practices for ML/AI development, model operations, and data-quality standards • Mentor technical contributors across teams, elevating technical quality and accelerating development

• Design, build, and optimize data pipelines for reach, frequency, and audience measurement using PySpark and Snowflake • Develop and implement clean room measurement methodologies for privacy compliant audience analysis • Analyze media and audience datasets to identify trends, anomalies, and optimization opportunities • Collaborate with product, engineers and data scientists to deliver scalable solutions for advertising analytics • Communicate findings and recommendations to technical and nontechnical stakeholders • Contribute to documentation, best practices, and process improvements

• Collaborate with multidisciplinary teams, communicating effectively to achieve shared objectives. • Work on solving complex problems, developing creative and innovative solutions. • Use critical thinking to analyze data, identify patterns, and make evidence-based decisions. • Pursue continuous learning, adapting to new technologies and trends to enhance your skills and contribute to project success.