Manager, Data Sciences Marketing Operations

The Institute of Internal Auditors Inc.

Website: theiia.org
Job details:

Summary

The Data Science Marketing Operations Manager supports the execution and operationalization of marketing analytics and data science initiatives. This role partners with marketing, analytics, and technology teams to ensure data processes, reporting, and analytical workflows operation efficiently and consistently to support informed marketing decisions.

The Manager focuses on translating analytical requirements into repeatable processes, maintaining data integrity, and enabling timely insights that improve marketing performance. This role combines analytical capability with strong operational, organizational, and cross-functional collaboration skills.

ESSENTIAL DUTIES AND RESPONSIBILITIES include the following. Other duties may be assigned.

AI, Machine Learning & Predictive Modeling Execution

• Build and operationalize predictive models supporting churn prediction, renewal likelihood, engagement scoring, and member lifetime value.
• Develop and fine-tune machine learning models using supervised, unsupervised, and deep learning methods to improve forecasting accuracy.
• Design and implement LLM-driven solutions for summarization, content generation, insight extraction, and member sentiment analysis.
• Work with vector databases and embeddings to build models that identify semantic patterns in member communications, behaviors, and feedback.
• Automate model retraining, validation, and versioning, ensuring continuous improvement and relevance to changing member behavior.

AI/LLM Applications for Membership Insights

• Develop AI-powered tools that identify early churn risk signals from member interactions, case notes, behavioral logs, and community activity.
• Create LLM-based classification frameworks to categorize inquiry themes, sentiment, and intent at scale.
• Build intelligent assistants for marketing and membership teams that recommend campaigns, audience segments, and next-best actions.
• Leverage LLMs to accelerate persona updates, extracting patterns from qualitative feedback, survey responses, and external research.
• Use AI to enhance segmentation models, uncovering micro-segments and emerging member clusters.

Data Integration & Scalable Infrastructure

• Develop data pipelines and automated workflows that unify CRM, AMS, marketing automation, CDP, community, LMS, event platforms, and analytics tools.
• Integrate third-party and external datasets (firmographics, demographic overlays, industry benchmarks, economic indicators) into the unified data ecosystem.
• Design solutions that enable data synthesis across structured and unstructured sources, including chat logs, survey text, social data, PDFs, and emails.
• Build reusable data assets, feature stores, and model-ready datasets to support ongoing analytics and experimentation.
• Ensure data integrity, quality controls, and standardization across pipelines, transformations, and outputs.

Insight Production, Dashboards & Enablement

• Create dynamic dashboards and automated insights for marketing, membership, product, and executive teams using tools like Power BI, Tableau, or Looker.
• Operationalize persona usage by converting strategic personas into computable, data-driven segments accessible across systems.
• Develop AI-generated insight summaries that convert complex analytics into actionable recommendations for non-technical stakeholders.
• Automate reporting and alerting so teams are notified of emerging risks or opportunities in member behavior.
• Support experimentation frameworks, including A/B tests, multivariate tests, and journey optimization powered by AI insights.

Cross-Functional Collaboration & Technical Leadership

• Partner with marketing teams to deploy personalization, predictive scoring, and AI-based content targeting inside MarTech platforms.
• Collaborate with product and digital teams to integrate predictive models and AI insights into digital experiences, portals, and self-service tools.
• Coordinate with IT and engineering on data architecture, API strategies, security, and system performance.
• Provide technical mentorship to analysts, data engineers, and junior data scientists, supporting skill development in AI and ML techniques.
• Champion is responsible for AI standards, ensuring fairness, transparency, data privacy, and alignment with organizational policies.

CORE COMPETENCIES

Education & Experience

• Typically, 5+ years’ experience
• Bachelor’s degree required.

Marketing Analytics Operations

• Supports day-to-day execution of marketing analytics and data science workflows.
• Ensures reliable delivery of dashboards, reports, and performance insights.
• Coordinates analytical requests and priorities across marketing teams.

Data Management & Quality

• Monitors data accuracy, completeness, and consistency across marketing systems.
• Supports documentation, data definitions, and reporting standards.
• Identifies and resolves data quality or process issues.

Communicative Competence

• Communicates analytical findings clearly and accurately to non-technical stakeholders.
• Translates data, metrics, and trends into actionable insights that support marketing decisions.
• Ensures clarity and consistency in how performance results are shared.
• Produces clear documentation, summaries, and process guides related to analytics and reporting.
• Ensures written materials are accurate, organized, and easy to understand.

Reporting & Presentation

• Develops clear, well-structured dashboards, reports, and presentation materials.
• Presents performance updates and insights in a concise manner.
• Highlights key takeaways, implications, and next steps.

Communication, Stakeholders & Visibility

• Communicates & teams across functions.
• High-level proficiency in critical communication skills.
• Strengthens and fosters internal and external relationships.
• Speaks to smaller groups in area of specialty.

Analytical Thinking & Problem Solving

• Manages and resolves operational, functional and organizational problems.
• Solves complex problems by taking a new perspective on existing solutions; exercises judgement based on the analysis of multiple sources of information.

Knowledge & Skills

• Requires understanding and application of procedures and concepts within own discipline and basic knowledge of other disciplines.
• Anticipates business and regulatory issues; recommends product, process or service improvements that will elevate and distinguish The IIA.
• Key skills: industry knowledge, talent management, problem solving, communication.

Supervisory Responsibilities

Carries out supervisory responsibilities in accordance with the organization's policies and applicable laws. Responsibilities include interviewing, hiring, and training employees; planning, assigning, and directing work; appraising performance; rewarding and disciplining employees; addressing complaints and resolving problems.

Language Skills

Ability to respond to common inquiries or complaints from members, customers, volunteers, and individuals in the broader business community. Ability to consolidate data from a wide variety of sources, interpret its meaning, and present such information in a meaningful way to top management and/or volunteers.

Reasoning Ability

Ability to solve practical problems and deal with a variety of concrete variables in situations where only limited standardization exists. Ability to interpret a variety of instructions furnished in written, oral, diagram, or schedule form.

Computer Skills

Expert ability to work in a computerized environment with knowledge of Microsoft Office products. Web-related computer skills listed above.

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