Sr. Product Manager, AdTech, Audiences & Trends

Clarvos LLC•Charleston, SC

5d•Remote

About The Position

The Senior Product Manager - AdTech, Audiences & Trends will lead the strategy, development, and execution of AI-powered products that help marketers discover high-value consumer segments, understand emerging trends, and activate campaigns across major advertising platforms. This role sits at the intersection of AdTech, consumer intelligence, data products, AI/ML, and customer experience. The ideal candidate has hands-on experience creating and evolving audience segments using machine learning, small and large language models, behavioral signals, demographic data, psychographic attributes, contextual signals, and first- and third-party data. This person understands how audience taxonomies, identity resolution, modeling, scoring, activation, and measurement work together to produce trusted and actionable marketing outcomes. This is a high impact, customer-informed product role for a self-starter who can move between market discovery, data analysis, model behavior, product requirements, campaign workflows, and executive communication. The Senior Product Manager will partner with Engineering, AI/ML, Design, Customer Success, Sales, and Marketing to turn complex data into intuitive products that improve audience quality, campaign performance, adoption, and customer value.

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.

Nice To Haves

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.

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.