Lead Data Scientist at Experian

The Data Science Lead will manage and mentor analytics team members while remaining hands-on with data science projects. Your role will involve leading EAMRM data science priorities, collaborating with cross-functional stakeholders, and ensuring alignment with regulatory and governance standards. You will also support innovation in GenAI and platform analytics, leveraging big data cloud platforms and advanced modeling techniques. You will report to the Director of Data Science and Gen AI.   What you'll do: • Lead and guide a team of innovation-focused data scientists. Partner with Leaders, Analytic Consultants, Engineers, Account Executives, Product Managers, and external partners to bring new innovative solutions to market that provide impact to Experian's broad client base • Technical Execution-Develop and deploy models using Python or PySpark on big data cloud platforms (e.g., Ascend).Ensure adherence to model risk management and governance processes. • Innovation & Strategy-Support GenAI and platform analytics innovation projects. Craft advanced machine learning analytical solutions and prototypes to extract insights from diverse structured and unstructured data sources. Articulate model processes and outcomes, documenting and presenting findings and performance metrics, and translating complex findings into actionable insights. • Collaborate with Engineering, Research, and Data Science teams in the design and implementation of Machine Learning, Dashboarding, Ad Hoc Analysis and AI applications in a cloud-native big data (AWS) computing platform. • Leverage Gen AI and model development tools to develop and maintain new models. Dissect and document vast datasets, analyzing them to highlight patterns and insights. Develop and assess analytic tools developed internally and externally. • Stay informed about regulatory changes, technological advancements, and model risk management processes and controls to ensure the technology stack meets all compliance requirements. Research, integrate, and test new data assets and software from different sources into Experian's analytic platform. • Gather feedback from internal and external clients to guide new product development, feature prioritization, and product evolution of tools and capabilities.