Senior Data Analyst, Early Onboarding & Engagement

SimplePractice

About The Position

SimplePractice is seeking a technical, growth-minded Senior Data Analyst to own the data strategy for the "First Mile" of the customer journey. Reporting through the Marketing organization, you will be the analytical engine driving our first 90-day experience. Your mission is to work with Product and Marketing by optimizing how new users discover, adopt, and habituate to our platform. You will manage our library of High-Value Actions (HVAs), refine our onboarding health scores, and leverage cutting-edge AI tools to accelerate customer "time-to-value."

Requirements

8+ years of experience in data analysis, with a heavy focus on product analytics, growth marketing, or customer lifecycle management in a SaaS environment.
Modern Technical Stack: Expert-level SQL and Python skills, with significant experience working in Snowflake and Tableau.
Product Analytics Expertise: Deep hands-on experience with Mixpanel to analyze user behavior, conversion funnels, and retention cohorts.
Developer-Lite Mindset: Comfortable using Git/GitHub and modern AI-coding environments (e.g., Cursor) to write production-adjacent Python code and automate data workflows.
AI Proficiency: You are an early adopter of AI tools. You have experience leveraging LLMs and automation platforms (e.g., n8n, Claude) to enhance your analytical throughput.
Experimental Rigor: Proven track record of designing, executing, and interpreting A/B tests and causal inference models in a fast-paced environment.

Nice To Haves

Master’s degree in a quantitative field (Data Science, Statistics, Mathematics, etc.).
Experience with Iterable (Marketing Automation) and Appcues (In-app engagement).
Experience building or maintaining "Health Scores" or "Propensity Models" for early-stage users.
Experience working alongside Data Scientists to deploy and test predictive models (e.g., Propensity or Next-Best-Action models).
Background in a high-growth B2B or Prosumer SaaS company.
Experience with performance marketing teams, GTM functions, and acquisition strategies
Familiarity with modern data science workflows, including version control and MLOps.

Responsibilities

Own the Onboarding Lifecycle: Drive the data strategy for the first 90 days of the customer journey, identifying friction points and opportunities for growth across both in-app and out-of-app touchpoints.
Manage & Evolve HVAs: Lead the continuous development of our High-Value Actions. You will track these metrics and statistically validate new behaviors that correlate with long-term retention.
Operationalize Predictive Models: Partner with our Data Science team to analyze and take advantage of our "Next Best Action" model. You will turn model outputs into actionable "nudges" and experiments.
Refine Engagement Scoring: Enhance our existing onboarding and engagement scores, developing more nuanced views of customer health that signal when a user is thriving or at risk of stalling.
Omnichannel Experimentation & Incrementality: Partner equally with Product and Marketing teams to design and analyze A/B tests across the product UI (Appcues) and marketing channels (Iterable). You will move beyond simple correlation to determine which touchpoints truly drive incremental growth.
AI-First Workflow: Actively use and experiment with AI tools (e.g., Claude Code, Cursor, n8n) to automate insights, build agentic workflows, and maintain a "developer-lite" approach to data tasks.
Dual-Platform Reporting & Enablement: Maintain a high-fidelity "Source of Truth" in Mixpanel and Tableau. You will also drive data literacy by training these teams to navigate these tools independently for day-to-day insights.
Data Stewardship: Act as the primary steward for onboarding data quality; proactively identifying tracking gaps in the 90-day funnel and partnering with Engineering to ensure event accuracy.