Responsibilities

• AI & Behavioral Analytics Leadership - Apply AI and machine learning — including LLMs and generative techniques — to accelerate segmentation, synthetic data generation, qualitative-to-quantitative synthesis, and automated insight generation.
• AI & Behavioral Analytics Leadership - Design and execute behavioral analytics engagements: clickstream analysis, passive behavioral data, digital journey mapping, engagement modeling, propensity and churn prediction, and customer lifetime value.
• AI & Behavioral Analytics Leadership - Integrate behavioral signals — from CRM, CDP, digital, transactional, and survey sources — into unified analytical frameworks that reflect how customers actually make decisions.
• AI & Behavioral Analytics Leadership - Lead technical execution in Python or R across the full modeling lifecycle: feature engineering, model selection, validation, interpretation, and deployment planning.
• AI & Behavioral Analytics Leadership - Stay current on advances in AI, machine learning, and behavioral science — identifying what's practically useful for clients versus what's hype.
• Client & Strategic Leadership - Own the analytical workstream end-to-end: converting business questions into clear analytic plans, timelines, and decision-ready outputs.
• Client & Strategic Leadership - Deliver executive-ready narratives that connect behavioral findings to marketing actions and measurable business outcomes.
• Client & Strategic Leadership - Serve as a trusted subject matter expert — explaining complex methods, defending recommendations, and redirecting analyses that won't answer the underlying question.
• Client & Strategic Leadership - Partner across research, strategy, technology, and data engineering to build solutions that can be activated in client environments.
• Client & Strategic Leadership - Support business development by shaping analytical approaches, scoping work, and contributing to proposals.

Requirements

• 7–10+ years in data science, marketing analytics, or quantitative research — agency, consulting, or in-house.
• Solid grounding in model validation, data quality, and the practical tradeoffs of applying analytics to real business decisions.
• Working knowledge of SQL and cloud data environments (Snowflake, BigQuery, AWS).
• Bachelor's degree in statistics, data science, economics, computer science, or a related quantitative field; advanced degree preferred.

Preferred

• Experience operationalizing models in CRM, CDP, or marketing automation platforms (Salesforce, HubSpot, mParticle, Braze, or similar).
• Familiarity with passive behavioral or digital measurement data providers.
• Experience designing agile test-and-learn programs and measuring incremental impact.
• BI/visualization tools: Tableau, Power BI, or Looker Studio.