Job description

Who We Are Good Inside is redefining parenting - not as something that should “just come naturally,” but as a skill to learn and practice. Founded by Dr. Becky Kennedy and Dr. Erica Belsky, we combine sturdy leadership with innovative technology to give parents personalized guidance, AI-powered support, and a global community. Our mission: help parents raise resilient, confident kids in a changing world. We’ve already reached millions, and we’re just getting started. We’re refining our product and expanding our reach to empower even more families. We’re looking for bold, high-ownership problem-solvers who want to build something new, tackle big challenges, and be at the forefront of change. The Opportunity Good Inside is seeking a Senior Analytics Engineer to own the data foundation behind our product. You'll build the models, tracking, and pipelines that tell us how parents discover, adopt, and keep coming back to Good Inside, and you'll use them to answer Product's most important questions yourself. This is a full stack role, weighted toward analytics engineering. You'll design production-grade dbt models for product events and subscription data, own our Amplitude instrumentation and tracking plans, and keep data fresh, tested, and trusted. Because you'll sit close to Product, you'll also turn that foundation into analysis, experiment readouts, and recommendations, using statistical methods when a question needs more than a dashboard. You'll be the bridge between Product, Engineering, and the Data team, so tracking and metrics are built in from the start rather than patched in after launch. This role is ideal for someone who thinks like a software engineer, has embedded with product teams at a subscription business, leverages AI-assisted workflows to move faster, and takes pride in clean systems that change what gets built. This is a hybrid role based in Manhattan with three days onsite. What You’ll Own Build the Product Data Foundation Design and maintain clean, modular dbt models for product events, engagement, and the member journey, from onboarding and activation through retention. Create well-documented transformations so Product trusts the numbers. Build Tracking and Instrumentation Maintain our Amplitude event taxonomy and tracking plans. Partner with PMs and engineers so new features ship with the right events, and keep definitions consistent across app and web. Model Subscription Data Model the subscription lifecycle (trials, conversions, upgrades, churn, reactivations) and connect it to product behavior, aligned with Engineering and Finance. Protect Data Quality Set up testing, monitoring, and alerting. Catch inconsistencies early, improve freshness, and make sure teams aren’t waiting on or questioning the data. Turn Data into Product Decisions Answer Product’s highest-impact questions directly: funnel and cohort analysis, experiment readouts, and churn or propensity models when a question calls for it. Lead with a clear recommendation. Enable Self-Serve Build the semantic layer and dashboards in Omni and Amplitude so Product can answer routine questions without waiting on Data. Partner and Influence Work closely with Product, Engineering, and the Data Analytics team, weigh in on architecture decisions with downstream data impact, and mentor others on the team. Balance competing priorities without lowering the bar. Your Skills & Experience 8+ years in analytics engineering, data engineering, or product analytics roles, with at least 2 supporting a product team Deep hands-on dbt experience in production Expert SQL and strong Python for modeling, pipelines, and analysis Experience with a modern data warehouse (Snowflake) and orchestration and ingestion tools (Airflow, Fivetran, or similar) Deep experience with event-driven product data and Amplitude (or Mixpanel, Heap), including owning event taxonomy and tracking plans Strong understanding of subscription businesses: trial conversion, retention cohorts, LTV, churn, and Stripe or app store billing data A track record of analysis that changed what got built, plus solid grounding in experimentation and statistics Experience designing clean, modular, well-tested data models for analytics use Proficient with Git and collaborative engineering workflows Make sound architectural decisions without heavy oversight, balancing speed with long-term maintainability Embrace AI-assisted development tools to increase velocity while keeping a high bar for accuracy Clear communicator who leads with a recommendation and thrives in fast-moving environments Bonus Points Direct-to-consumer subscription experience, especially with app store and web purchase flows and the gaps between them Data science experience: churn or propensity modeling, survival analysis, or causal inference Pricing, packaging, or paywall experimentation Mobile app analytics and attribution Familiarity with Segment, Braze, and BI semantic layers (Omni a plus) Experience mentoring analysts or teaching stakeholders to self-serve What We Offer Compensation: Annual salary for this role will be $185k – $195k Company Equity Comprehensive benefits package 401k + Company match Time off to recharge Hybrid work environment A high-ownership, high-performance, high-collaboration culture Equal Employment Opportunity Good Inside is an equal opportunity employer and as such, we do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other characteristic protected by applicable laws. We are dedicated to growing a diverse team of highly talented people. As much as we believe in focusing on the parent behind the parenting and the child behind the behavior, we believe in focusing on the person behind the job. We’re dedicated to building a workplace where we give each other the strategies, support, and space we each need to thrive—believing in and bringing out the good inside of everyone.. If you require any accommodations during the recruitment process, whether it be alternate forms of material, accessible meeting rooms, etc., please let us know and we will work with you to meet your needs. For information about Good Inside's privacy practices, see our Privacy Policy . California applicants, please also see our CA Applicant Privacy Notice .

Requirements

Must-haves

None extracted.

Nice-to-haves

Direct-to-consumer subscription experience, especially with app store and web purchase flows and the gaps between them
Data science experience: churn or propensity modeling, survival analysis, or causal inference
Pricing, packaging, or paywall experimentation
Mobile app analytics and attribution
Familiarity with Segment, Braze, and BI semantic layers (Omni a plus)
Experience mentoring analysts or teaching stakeholders to self-serve

Application prep

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Benefits

Benefits detected in the listing.

401k