Senior Lifecycle Marketing Manager | New York, NY

Talkiatry•New York, NY

1d•$145,000 - $185,000•Onsite

About The Position

We are seeking a Senior Lifecycle Marketing Manager to own measurable performance improvements across the full patient lifecycle, spanning onboarding, activation, early care, and long-term retention. This is a high-impact, highly visible role at a critical moment in Talkiatry's growth, sitting at the intersection of data, experimentation, and patient experience. You will design, execute, and analyze experiments and targeted initiatives to improve intake and activation rates, accelerate early care progression, and strengthen ongoing engagement. You will bring an experimentation-first mindset and a genuine curiosity for how emerging AI and machine learning capabilities can accelerate lifecycle performance, from smarter segmentation to predictive engagement. You will work closely with Operations, Product, Data Engineering, Marketing Operations, and Creative to enable event-driven programs, optimize lifecycle performance across channels, and reduce operational friction across the patient and provider lifecycles.

Requirements

5 to 8 or more years of experience in growth, lifecycle, or performance marketing with a track record of driving measurable outcomes
Strong SQL proficiency and comfort operating in data warehouses, with Snowflake experience preferred
Experience designing, measuring, and iterating on structured experiments, with a clear understanding of what incrementality means and why it matters
Deep familiarity with cohort analysis, funnel diagnostics, and segment-level performance variation
A genuine curiosity about AI and ML applications in lifecycle marketing, including predictive modeling, dynamic content, propensity scoring, and intelligent automation, paired with the analytical rigor to evaluate them critically rather than adopt them uncritically
Comfort testing and forming opinions on new tools quickly, without waiting for a perfect use case to start learning, and the ability to separate real lift from noise
Strong problem-solving skills and the ability to translate complex data into clear, concise business recommendations that influence prioritization and strategy

Responsibilities

Design and execute structured A/B and multivariate tests across email, SMS, and in-app channels, building experimentation roadmaps tied directly to lifecycle KPIs like No show late cancel, visit completion, and retention
Analyze funnel performance to identify gaps, diagnose segment and state-level variation, and translate findings into prioritized, data-backed improvements
Actively test and evaluate AI-powered capabilities within the lifecycle stack, including send-time optimization, predictive segmentation, dynamic content, and propensity modeling, treating each as a hypothesis to be validated rather than a feature to be adopted
Partner with Data, Engineering, and Operations to integrate machine learning signals, including no-show risk, churn risk, and engagement propensity, into lifecycle triggers and journeys in ways that are measurable and incrementally proven
Bring analytical rigor and healthy skepticism to AI outputs, validate model performance, monitor for drift, and ensure AI-assisted decisions are always grounded in patient outcomes and business impact
Own the analytical layer for lifecycle performance, building, maintaining, and evolving reporting frameworks and dashboards that give the team a clear, real-time view of lifecycle health
Write SQL queries and partner with Analytics and BI teams to surface actionable insights from patient behavior, funnel performance, and experiment results
Set the measurement standard for the team by defining success metrics, ensuring proper instrumentation, and holding experiments to an incrementality bar before results are acted on
Diagnose state-level and segment-level performance variation to identify where the lifecycle is working and where it needs attention
Lead through influence across Product, Operations, Marketing Operations, Data Engineering, and Creative, driving alignment across technical and non-technical stakeholders on shared lifecycle priorities
Partner with Technical Lifecycle and Marketing Operations to design, instrument, and launch experiments with the right data infrastructure in place
Collaborate with Creative on messaging hypotheses, bringing behavioral data and patient insights to inform content strategy
Align with Product and Product Marketing to integrate behavioral and product signals into lifecycle programs, ensuring the patient experience is coherent across channels