Senior Director of Software Engineering
New Yesterday
As a Senior Director of Software Engineering at JPMorgan Chase within the Cybersecurity and Tech Controls team, you will leverage your expertise in designing and developing sophisticated modelling software to enhance cyber and business resiliency efforts. Collaborating closely with a quantitative data scientist, you will spearhead the creation of a Bayesian inference-based modelling platform aimed at forecasting the risk and business consequences of potential disruptive events. This pivotal role plays a crucial part in guiding strategic decisions related to cyber defence, business continuity planning, regulatory compliance, and operational resilience.
Leads multiple technology and process implementations across departments to achieve firmwide technology objectives
Provides leadership and high-level direction to teams while frequently overseeing employee populations across multiple platforms, divisions, and lines of business
Design and develop scalable, production-grade software for risk modelling, inference engines, and simulation frameworks
Collaborate with cybersecurity teams, risk analysts, data scientists and resiliency stakeholders to define model inputs, risk scenarios, and system architecture requirements
Bayesian networks, probabilistic graphical models) into performant software modules.
Develop data ingestion and transformation pipelines to source data from internal systems and threat intelligence sources
Lead the architecture design for modular, explainable, and extensible risk modelling systems
Ensure robustness, auditability, and version control of all models and underlying code per company and regulatory standards
Build APIs and tools that enable integration with business intelligence dashboards, threat platforms, GRC systems and reporting pipelines
Partner with enterprise risk and enterprise control management teams to ensure the model outputs are interpretable and actionable for executive decision-makers
Formal training or certification on software engineering concepts and expert applied experience. Experience leading complex projects supporting system design, testing, and operational stability
Strong programming skills in Python (especially scientific libraries: and experience working with probabilistic programming frameworks (e.g. Experience designing and deploying Bayesian networks, Monte Carlo simulations, or other probabilistic models in complex real-world systems.
Demonstrated experience developing enterprise-scale data modelling platforms or risk analysis tools
Solid knowledge of software architecture principles, cloud-native design (e.g. AWS/GCP), containerization (Docker, Kubernetes), and CI/CD best practices
Strong academic background with an advanced degree in either Mathematics, Data Science, Engineering, Computer Science or another quantitative field.
Background in graph theory, decision theory, or risk quantification is a plus
Understanding of cybersecurity risks, operational resilience, or business continuity frameworks in regulated industries (preferably financial services)
Experience in modelling cascading failures, supply chain risk, or complex interdependency networks
- Location:
- London
- Job Type:
- FullTime
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