Senior Product Scientist (Agentic Growth & Marketing)

TL;DR

Senior Product Scientist (Agentic Growth & Marketing) (AI): Building and operating a closed-loop agentic marketing system that connects real-time member and campaign signals to evidence-based decisions across paid acquisition and lifecycle engagement. Focus on shipping member-facing prototypes and lightweight experiments, implementing causal measurement for true incremental lift, and governing autonomous budget/creative and messaging decisions with SQL/Python-powered data pipelines and model evaluation.

Location: Remote (New York City, NY); Remote (Seattle, WA); Remote (United States); San Francisco, CA (Hybrid). Candidates must permanently reside in the US full-time.

Salary: $122,400-$170,000 base + equity + benefits (location-based range applies for SF/NYC/Seattle).

Company

hirify.global provides lifelong mental health support through evidence-based content, clinical care, and technology.

What you will do

• Own and execute the agentic paid media optimization system, including decision logic for budget reallocation, channel performance monitoring, and ad creative rotation.
• Execute the agentic lifecycle marketing strategy by implementing decision policies, managing an approved content/action library, and triggering personalized communications via Braze within safety guardrails.
• Define and manage data/feature requirements so member behavioral signals and model outputs (e.g., churn risk, LTV) reliably power agentic decisions.
• Maintain autonomy with governance guardrails, including budget checks, brand safety points, and audit logging aligned with Legal, Privacy, and Clinical requirements.
• Implement causal measurement plans to connect agent decisions to member outcomes and improve decision policies using measurable incremental impact.
• Build the marketing measurement foundation (incrementality testing infrastructure, cross-channel attribution, identity resolution, and event logging) and communicate product requirements/status to Engineering and Data Science.

Requirements

• 3+ years of experience in product science, data science, or a related field, with a track record of shipping product features/systems in production.
• Experience shipping experiments that learn from member signals, including practical execution of marketing automation features or agentic AI prototypes in a cross-functional team.
• Strong hands-on technical depth in SQL and Python, including building proofs of concept and contributing to data pipelines and feature engineering.
• Deep experience with lifecycle marketing execution and integrating with Braze (or similar CRM) via API for event-driven personalized communications at scale.
• Solid understanding of paid media measurement/optimization, including incrementality testing, media mix modeling, and identity resolution/event logging for cross-channel causal measurement.
• US residency requirement: must permanently reside in the US full-time.

Nice to have

• Experience with reinforcement learning, contextual bandits, or LLM-based real-time personalization using lightweight experiments.
• Experience building automation/custom AI tools to reduce team toil and speed experimentation.
• Experience with causal inference methods (holdout/geo experiments, synthetic control) for marketing measurement/personalization evaluation.
• Experience with GDPR/CCPA/ATT in marketing automation or agentic AI infrastructure.
• Experience in digital health, consumer subscription, or direct-to-consumer contexts where LTV/retention and clinical safety matter.

Culture & Benefits

• Mission-driven work focused on mental health support and responsible AI.
• Hybrid model for candidates with primary residence in the greater SF area: 3 days/week in office; flexibility for the rest of the week.
• Competitive compensation: base salary, equity, comprehensive healthcare coverage, monthly wellness stipend, and retirement savings match.
• Lifetime hirify.global membership and generous parental leave.
• Values-based collaboration and experimentation with care and clear communication across functions.

Hiring process

• Recruiter shares details about the hybrid model (if applicable) and the location-based compensation range.
• Interviews evaluate technical execution (SQL/Python, causal measurement, agentic decision systems) and cross-functional communication.
• Final steps include discussions aligned with role requirements and production readiness.