Sr. Specialist, Audience Intelligence & Analytics

Our client, a Leading International Consumer Goods company, is looking for a Sr. Specialist, Audience Intelligence & Analytics for their Remote location.

Responsibilities:

• Audience & Segmentation Analytics
• Conduct audience sizing, profiling, overlap, penetration and movement analysis across priority consumer segments.
• Evaluate behavioral, demographic, transactional, engagement, loyalty and channel characteristics that differentiate audiences.
• Assess segment quality, distinctiveness, activation potential and downstream performance.
• Analyze audience overlap across campaigns and journeys to support prioritization and reduce unnecessary consumer contact.
• Support development and evaluation of rule-based, modeled and partner-enriched audiences.
• Partner with Audience Intelligence leads, ID&A and external partners to translate audience findings into actionable targeting and activation recommendations.
• Audience reporting and measurement
• Automate repeatable analysis and reporting workflows to reduce manual preparation and increase time available for deeper analytical work.
• Monitor audience size, growth, reach, activation and funnel performance; identify trends, anomalies and opportunities requiring deeper analysis.
• Prepare clear performance summaries and leadership-ready insights that explain what happened, why it matters and what action should follow.
• Audience, campaign and journey analytics
• Analyze audiences using behavioral, demographic, transactional, engagement and channel data.
• Measure activation across CRM, web, media, loyalty, retail, CSC and other consumer channels, including funnel progression and test/control results where applicable.
• Connect audience performance to key lifecycle stages, including acquisition, trial, onboarding, engagement, conversion, loyalty, retention and reactivation.
• Predictive & AI-Enabled Audience Analytics
• Support analysis and business measurement of propensity models, recommendation engines, Next Best Action and AI-enabled audience solutions.
• Evaluate model-selected audiences against business-as-usual or rule-based audiences where appropriate.
• Track audience volumes, activation rates, conversion, incremental performance and lifecycle outcomes.
• Escalate material data or performance changes to the appropriate model, data or business owner.
• Support analytical use cases that improve the speed, accessibility and repeatability of audience insights.
• Data Quality, Business Requirements & Continuous Improvement
• Perform ongoing data-quality validation across CDP and consumer data, identifying missing, inconsistent, duplicated, stale or unexpected data that could affect audience segmentation, activation and measurement.
• Monitor critical consumer attributes, audience logic and data flows to identify issues before they impact downstream campaigns, analytics or consumer experiences.
• Translate business needs and use cases into clear data and technical requirements, including required attributes, business rules, acceptance criteria and expected outcomes.
• Serve as a bridge between Consumer Experience and technology/data teams, ensuring business requirements are understood, technically feasible and implemented as intended.
• Coordinate investigation and resolution of data-quality issues with CDP, ID&A, technology and other relevant teams, and validate fixes from a business and data perspective before closure.
• Maintain clear documentation of data definitions, business rules, data dependencies, known issues and quality-control procedures.
• Identify opportunities to improve data reliability, monitoring, automation and issue-detection processes across audience and consumer-data use cases.
• Key Deliverables During the Engagement
• Audience Intelligence & Analytics: Audience sizing, profiling, segmentation, overlap, lifecycle and performance analysis.
• Activation & Journey Measurement: Measurement connecting priority audiences to activation, engagement, conversion, loyalty and retention outcomes.
• CDP Data Quality & Validation: Proactive monitoring and validation of consumer attributes, audience logic and critical data flows.
• Analytics Automation: Reusable SQL, Python, dashboards and automated analytical processes that reduce manual work and accelerate insights.
• Predictive Analytics Support: Evaluation and monitoring of segmentation, propensity and AI/model-driven audiences and their business performance.
• Business Translation & Requirements: Actionable insights and clearly defined data/technical requirements that bridge business needs with CDP, ID&A and technology teams.
• Engagement Profile
• This is a contractor role designed to provide dedicated reporting, analytics and measurement capacity. The role does not include permanent employee status, direct people leadership, enterprise AI strategy ownership, final governance accountability, budget ownership or investment decision rights.

Requirements:

• Approximately 4-7 years of relevant experience in advanced analytics, consumer analytics, marketing analytics, audience intelligence, data science, CRM analytics or a related field.
• Bachelor's degree in Data Science, Statistics, Analytics, Computer Science, Economics, Business, Marketing, Information Systems or a related discipline, or equivalent relevant professional experience.
• Advanced proficiency in SQL, with demonstrated experience querying, joining, transforming and analyzing large, complex consumer or behavioral datasets. SQL will be a core part of the contractor's day-to-day responsibilities.
• Strong experience conducting consumer and audience analytics, including segmentation, profiling, behavioral analysis, funnel analysis, cohort analysis, targeting and activation measurement.
• Working knowledge of machine learning and predictive analytics, with experience interpreting and evaluating outputs from models such as propensity, classification, clustering, recommendation or similar consumer-focused models.
• Experience using analytical methods to identify consumer patterns, drivers, opportunities and actionable audience insights, rather than solely producing recurring reports.
• Experience developing KPI frameworks, analytical measurement approaches and performance reporting across consumer journeys, campaigns, audiences or loyalty programs.
• Proficiency with data visualization and business intelligence tools such as Power BI, with strong ability to communicate complex analytical findings clearly to both technical and non-technical audiences.
• Strong business acumen and analytical storytelling skills, with the ability to translate business questions into analytical approaches and convert findings into clear implications and recommended actions.
• Experience partnering across business, analytics, data science and technology teams, including translating business needs into data and analytical requirements.
• Strong attention to data quality, analytical rigor, documentation and reproducibility, with the ability to independently identify and investigate unexpected data or results.
• Ability to manage multiple analytical priorities independently in a fast-paced, cross-functional environment.
• Experience with CRM, CDP, marketing automation, audience activation or digital analytics platforms.
• Experience working with first-party consumer data, Consumer 360 datasets or online and offline data integration, Treasure Data preferrable.
• Experience measuring omnichannel campaigns, loyalty programs, lifecycle journeys or predictive-model use cases.
• Familiarity with data privacy, data governance, model monitoring and Responsible AI concepts.
• Experience in consumer products, retail, e-commerce, loyalty, regulated industries or enterprise environments.
• Core Capabilities
• Capability What Success Looks Like
• Analytical rigor Produces accurate, reproducible analysis and identifies material data issues before distribution.
• Business translation Converts technical findings into concise implications and recommended actions.
• Reporting discipline Delivers consistent, on-time reporting with documented definitions and methods.
• Cross-functional partnership Aligns business and technical stakeholders around data needs, KPIs and interpretation.
• Continuous improvement Automates repetitive work and improves reporting speed, usability and reliability.

Why Should You Apply?

• Health Benefits
• Referral Program
• Excellent growth and advancement opportunities