Senior Growth Analyst - Spark

readdle70; United States; Remote; USD 120,000 - 170,000; Full time

Job summary

readdle70 is seeking a senior analytics professional embedded with a personal productivity app on Apple platforms. You will own the numbers behind user acquisition, engagement, and long-term retention, translating complex data into clear insights that shape product and marketing decisions across the full user lifecycle.

You will analyze funnels, build dashboards, design events for new features, run experiments, and develop forecasting models to guide quarterly prioritization and pricing

Qualifications

• 5+ years in growth, product, or marketing analytics in B2C or SaaS.
• Experience with user acquisition, pricing, monetization, or migration for subscriptions.
• Strong SQL and data-warehouse experience.

Responsibilities

• Analyze user acquisition, engagement, and retention across the full lifecycle.
• Build self-serve dashboards providing a single source of truth for growth metrics.
• Design and QA event structures for features, campaigns, and experiments.
• Forecast installs, conversions, retention, and revenue.
• Surface hypotheses and growth opportunities to product and marketing teams.

Skills

SQL

BigQuery

Amplitude

Tableau

Looker

Python

R

statistics

experimentation

funnel analysis

cohort analysis

segmentation

business acumen

strategic thinking

Tools

Tableau

Looker

Amplitude

Mixpanel

Heap

Hotjar

PostHog

Job description

Role overview

A senior analytics role embedded with a personal productivity application on Apple platforms, owning the numbers behind user acquisition, engagement, and long-term retention. The position blends hands-on data work with strategic influence, turning complex datasets into clear insights that shape product and marketing decisions across the full user lifecycle.

Responsibilities

• Transform and analyze large datasets in BigQuery and Amplitude to surface growth opportunities, trends, anomalies, and actionable insights across the user journey.


• Build and maintain self-serve dashboards and reports that establish a single source of truth for key growth metrics.


• Design, document, and QA event structures for new features, campaigns, and experiments, and develop monetization measurement systems that support pricing and migration decisions.


• Analyze funnels spanning ads, app store, onboarding, in-app usage, purchases, and cancellations to identify drop-offs and growth levers.


• Plan, sequence, and monitor A/B experiments and feature launches, validating statistical rigor and tracking consistent long-term impact.


• Proactively surface hypotheses and growth opportunities to product and marketing teams, shaping quarterly prioritization through impact scenarios and roadmap influence.


• Build forecasting and scenario models for installs, conversions, retention, and revenue.


• Maintain data integrity across tools and pipelines, partnering with attribution vendors to optimize acquisition reporting.

Requirements

• Five or more years in growth, product, or marketing analytics within a B2C or SaaS environment, including experience with user acquisition, pricing, monetization, or migration initiatives for subscription products.


• Strong SQL skills and hands-on experience with BigQuery or comparable cloud data warehouses such as Redshift or Snowflake.


• Proficiency with BI tools such as Tableau or Looker and with product analytics platforms such as Amplitude, Mixpanel, Heap, Hotjar, or PostHog.


• Familiarity with marketing attribution platforms such as AppsFlyer, Adjust, or Kochava, along with working knowledge of Python or R for analysis and automation.


• Solid grounding in statistics, experimentation, funnel and cohort analysis, segmentation, and modeling of churn or lifetime value.


• Demonstrated ability to act as a strategic thought partner to product and marketing teams rather than a request-driven executor, with strong business acumen and a proactive, curious, coachable mindset.

Nice to have

• Advanced analytics background such as causal inference, quasi-experiments, linear programming, or econometrics.


• Experience with machine learning or time-series modeling.

Benefits and work setup

• Customer-centric culture with opportunities to engage directly with end users whose feedback shapes product direction.


• Strong emphasis on ownership, mastery, and continuous learning, with feedback treated as a catalyst for growth.


• Collaborative team environment built on transparency, mutual care, and collective success.


• Opportunity to deliver measurable impact on products used by a large global audience.


• Environment that actively welcomes curiosity, creativity, and fresh ideas, turning them into real innovations.