Senior
Data & Marketing Systems Quant Analytics Lead-Senior Associate
Shape how marketing execution uses data—at scale and with strong controls—to deliver more relevant customer experiences. In this role, you will modernize targeting data, reduce manual reporting through automation, and improve reliability with proactive monitoring. You will partner across Product, Technology, and business stakeholders to bring measurable outcomes to life while enabling responsible use of artificial intelligence.
Job summary As a Data Management Lead in the Marketing Execution team, you will design and run data strategies that improve audience targeting, measurement, and operational efficiency. You will turn business needs into clear, testable requirements and repeatable datasets that support consistent delivery. You will implement monitoring and quality checks to detect issues early and protect performance. You will help teams adopt responsible “human-in-the-loop” ways of working for AI-supported execution. You will quantify and communicate value through cycle-time reduction, hours saved, and audience quality improvements.
You will help establish reusable audience frameworks and documentation that accelerate delivery and reduce rework. You will collaborate closely with Product and Technology to ensure new capabilities include clear controls, explainability expectations, and measurable success criteria. You will build strong relationships across workstreams and drive adoption of best practices for standardization and reusability.
Job responsibilities
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Develop and implement data management strategies for marketing execution, including AI-assisted data quality monitoring and automated operational reporting to reduce manual effort and improve reliability
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Leverage data from systems of record to refine targeting and optimize performance, incorporating advanced analytics and machine learning-informed insights (for example, propensity and suppression inputs) where approved
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Drive adoption of best practices for standardization and reusability of marketing data outputs, including reusable audience frameworks and generative AI-accelerated documentation (requirements, definitions, quality assurance checklists)
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Manage execution, monitoring, and quality of data initiatives to support message-driven audience targeting, including proactive issue detection through alerts and anomaly flags
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Collaborate with Product and Technology to orchestrate requirements and delivery plans for product development, omnichannel initiatives, and system implementations, ensuring AI-enabled capabilities have clear controls and measurable outcomes
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Build strong working relationships across workstreams and stakeholders, and help drive adoption of human-in-the-loop operating models that enable safe scaling of AI-supported execution
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Partner with business leadership to define priorities and oversee execution, including quantifying value from automation and AI (cycle-time reduction, business-as-usual hours saved, audience quality improvements, performance lift)
Required qualifications, capabilities, and skills
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Bachelor’s degree in Data Science, Statistics, Information Systems, or related field
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Experience in data analytics or customer segmentation, with ability to connect analytics outputs to campaign execution outcomes
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Proficiency with tools such as SQL, Python, Excel, Tableau, Adobe, and Segment, with ability to build repeatable datasets and automation-friendly outputs
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Ability to translate business requirements into technical specifications and communicate complex topics to non-technical partners
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Knowledge of digital marketing principles and measurement, with ability to run structured test-and-learn optimization
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Ability to build cross-functional relationships and drive change adoption across stakeholders
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Strong communication skills, including ability to explain AI-supported decisions and controls clearly and without jargon
Preferred qualifications, capabilities, and skills
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Experience in marketing operations and marketing technology, including familiarity with AI-enabled targeting or decisioning
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Proficiency in project management and agile tools (for example, Microsoft Project, Excel, PowerPoint, Jira, Confluence), with ability to run automation-first plans and track value realization
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Experience with customer data platforms and marketing automation tools (for example, Salesforce, Segment, SAS, Adobe, Microsoft), including incorporating model outputs into activation where permitted
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Experience working with agencies or consultancies, with ability to translate vendor capabilities into governed requirements suitable for a bank environment
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Ability to manage multiple initiatives under tight deadlines while maintaining quality through automation and AI-assisted analysis
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Strong relationship development and negotiation skills, including aligning partners on responsible AI use, governance needs, and measurable success criteria
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