Data Scientist & Automation Lead - Vulnerabilities remediation Governance

We are hiring a Senior Data Scientist to help drive high-impact Vulnerability remediation governance and oversight program with our customers and their partners, transforming our compliance missions using AI and other cloud-based solutions and services. Data scientists have data management and expertise in developing statistical techniques to analyse data and find patterns. You'll be part of the Vulnerability management oversight and governance Operations team, working within integrated operations squads to build and embed industrialised decision-support software products.

This area plays a critical role in improving operational compliance outcomes by applying advanced machine learning and optimisation techniques to real-world decision-making challenges across the State Street vulnerability remediation and governance teams.

• You will acquire the data necessary for vulnerability remediation and plan and develop usable data sets for modelling. You'll also update internal best practices for data collection and preparation, and contribute to data integrity conversations with stakeholders, management and threat and vulnerability management
• You will evaluate your team's models and recommend improvements as necessary, drive best practices for models, and develop operational models that run 'll also conduct thorough reviews of data analysis and modeling techniques, and identify and invent new evaluation methods.
• You will research and maintain a deep knowledge of the industry, including trends and technologies, so that you can identify strategy opportunities and contribute to thought leadership best practices. You'll also write extensible code that spans multiple features, and develop expertise in proper debugging techniques.
• You will define business, customer, and solution strategy goals, and partner with other teams to identify and explore new opportunities. You'll also apply a customer-oriented focus to understand their needs, and help drive realistic customer expectations.
• Act as the technical owner of one or more production-grade data science product codebases
• Lead the end-to-end delivery of decision-support software across the full product lifecycle
• Understand complex operational business problems end to end and identify opportunities for data-driven optimisation
• Drive modelling and system design decisions, balancing implementation time, system behaviour, technical debt and business value
• Prototype, build and deliver industrialised machine learning and optimisation models in Python
• Design and build robust data ingestion, cleaning and processing pipelines
• Implement orchestration pipelines and CI/CD deployment processes
• Ensure software quality through logging, error handling and automated testing
• Harden algorithms against operational and data edge cases
• Quantify product adoption and value capture
• Engage with business stakeholders to gather requirements and feedback
• Contribute to feature prioritisation and roadmap discussions
• Support integration of decision-support products into operational business processes
• Communicate modelling approaches, trade-offs and results clearly to technical and business audiences
• Mentor and support junior team members
• Contribute to agile ways of working, including Git versioning, code reviews and delivery predictability
• Strong experience in Data Science, Machine Learning, and Advanced Analytics to develop predictive, operational, and insight-driven solutions.
• Proficiency in Python, SQL, and Data Engineering for data transformation, modelling, automation, and analytics development.
• Strong proficiency in visualisation tools such as Power BI and Tableau to design interactive dashboards, self-service reporting tools, and stakeholder-ready business intelligence solutions.
• Strong problem definition and design thinking skills to convert ambiguous business needs into user-centered, scalable analytics and automation solutions.
• Comfortable working in ambiguous environments where business problems may not be clearly defined at the start; able to shape direction, ask the right questions, and create clarity with stakeholders.
• Working knowledge of Power Platform and Power Automate is desirable, particularly for workflow automation and rapid prototyping, but secondary to core data science, AI, analytics, and integration capabilities.
• Experience leveraging SharePoint, Microsoft 365, and enterprise collaboration technologies to deliver digital solutions and knowledge management capabilities.
• Proven ability to design and…