Sr. Product Manager, AdTech, Audiences & Trends

Clarvos is a company focused on leveraging AI-powered products for marketers, and they are seeking a Senior Product Manager for AdTech, Audiences & Trends. This role will lead the strategy, development, and execution of products that help marketers discover valuable consumer segments and understand trends across major advertising platforms.

Responsibilities:

• Define and execute the product vision, strategy, and roadmap for Audience Intelligence, Trend Discovery, and related campaign planning and activation experiences
• Own the end-to-end product lifecycle from audience and trend discovery and opportunity sizing through requirements, launch, adoption, measurement, and optimization
• Translate advertiser, and customer signals, and internal stakeholder needs into scalable product capabilities, clear priorities, and measurable business outcomes
• Design audience products that enable marketers to discover, analyze, compare, build, save, and activate consumer segments across their industry and competitor domains, and translate those into high impact campaign strategies
• Develop segmentation strategies using first-party, third-party, behavioral, transactional, demographic, psychographic, contextual, geographic, cultural, and interest-based signals
• Apply hands-on knowledge of AI and machine learning to define how models identify, cluster, score, rank, expand, suppress, and refresh audience segments
• Partner with AI/ML and Engineering to improve audience modeling, lookalike expansion, propensity scoring, identity resolution, feature selection, taxonomy design, and model evaluation
• Define AI-assisted and agentic workflows that recommend high-value audiences, explain segment composition, and support activation at a scale beyond manual analysis
• Build products supporting acquisition, prospecting, retargeting, suppression, lookalike audiences, lifecycle marketing, campaign optimization, and measurement
• Own products that identify emerging consumer, cultural, regional, seasonal, category, and platform-level trends from large-scale structured and unstructured datasets
• Define ranking methodologies, scoring systems, confidence thresholds, freshness rules, and experiences that explain why a trend or audience matters and how to act on it
• Translate audience and trend intelligence into campaign recommendations for targeting, messaging, creative direction, channel selection, and measurement
• Define detailed product requirements, user stories, acceptance criteria, data contracts, API behaviors, edge cases, and operational workflows
• Validate releases through product testing, data inspection, API verification, model-output review, and end-to-end workflow testing
• Identify data-quality issues, model anomalies, segment drift, activation failures, bugs, and customer-impacting defects; investigate root causes and drive resolution
• Establish metrics for audience quality, match and activation rates, segment adoption, insight engagement, campaign performance, satisfaction, and commercial impact
• Use product analytics, SQL-based analysis, campaign data, customer feedback, experiments, and market research to prioritize investments and validate hypotheses
• Drive alignment across Product, Engineering, Data Science, Design, Customer Success, Sales, Marketing, Legal, Privacy, and external partners
• Communicate strategy, priorities, tradeoffs, risks, technical constraints, roadmap changes, and outcomes to executive and cross-functional stakeholders

Requirements:

• 5 or more years of Product Management experience, preferably in AdTech, MarTech, AI/ML, consumer intelligence, identity, data platforms, or enterprise SaaS
• Demonstrated hands-on experience developing audience or consumer segments using AI, machine learning, statistical modeling, clustering, classification, propensity models, embeddings, or large language models
• Strong understanding of audience taxonomies, segmentation methodologies, lookalike modeling, targeting, suppression, identity resolution, data onboarding, activation, and measurement
• Experience working with first-party, third-party, behavioral, demographic, psychographic, contextual, transactional, and interest-based data
• Strong understanding of campaign planning, audience activation, optimization, measurement, advertising pixels, conversion APIs, publishers, and DSP workflows
• Experience partnering with AI/ML and Engineering on model requirements, feature definitions, training data, evaluation metrics, data pipelines, APIs, and production systems
• Ability to evaluate model outputs and audience quality using quantitative methods, customer evidence, performance data, and practical marketing judgment
• Proven experience writing detailed product requirements, technical specifications, user stories, acceptance criteria, data definitions, and edge cases
• Experience using analytics and experimentation to investigate issues, validate hypotheses, prioritize investments, and measure product impact
• Strong customer-facing skills and the ability to translate advertiser and agency workflows into scalable product solutions
• Exceptional communication, product storytelling, stakeholder management, and cross-functional leadership skills
• Demonstrated ability to operate independently, create structure in ambiguity, make informed tradeoffs, and drive initiatives from concept through launch
• Bachelor's degree in business, marketing, computer science, engineering, data science, statistics, economics, or a related field, or equivalent practical experience
• Experience building audience, identity, CDP, data marketplace, DSP, social listening, trend analytics, or consumer intelligence products
• Experience with agentic AI, generative AI, NLP, embeddings, vector search, knowledge graphs, or AI-assisted audience generation
• Working knowledge of SQL and experience exploring datasets, validating segment composition, or investigating campaign and product performance
• Familiarity with Python, R, notebooks, BI tools, or other analytical environments used for model and dataset exploration
• Experience with privacy-forward advertising, consent, data governance, clean rooms, identity alternatives, and evolving regulations
• Experience integrating with Meta Ads, Google Ads, Amazon Ads, The Trade Desk, StackAdapt, LiveRamp, or other audience and activation platforms
• Experience with attribution, incrementality, media measurement, conversion APIs, pixels, and probabilistic or deterministic identity approaches
• Experience in B2B SaaS or enterprise marketing technology and familiarity with advertiser, agency, and campaign-operations workflows