Head of Data Analytics

Title: Head of Data Analytics
Location: Remote

Company Overview

• App with over 85 million installs, aiming to become a connected care platform.
• Functioning like a startup with the stability of a public company; team size is 30-35.

Role Requirements

• Looking for a head of data analytics with strong analytics skills, not heavy on data engineering.
• Must have consumer app experience, familiarity with onboarding funnels, and consumer marketing.

Candidate Requirements

• Must be a strategic communicator, able to work with executives and tell data stories effectively.
• Needs to have experience in advanced analytics, SQL, and ideally some Python.

Ideal Candidate Profile

• Strong business sense, possibly with a consulting background; able to be a thought partner at the executive level.
• Should be a balanced player-coach, competent in managing a small team while being hands-on.

Pain Points

• Difficulty finding candidates who can bridge technical skills and executive communication.
• Challenge in aligning candidate expectations with the role''s strategic and hands-on requirements.

Interview Process

• Involves multiple stakeholders: head of engineering, head of product, and a data exercise.
• Series of 30-45 minute meetings to assess fit and skill level.

Seniority

• 6+ years of experience in data analytics for consumer products with experience leading teams
• Work experience
• 2+ years working in B2C mobile apps
• 2 - 5 years of direct management experience is the sweet spot – looking for a Player-coach
• Experience in a fast paced start-up environment (VC backed, rapidly growing mobile app, etc.)

Hard skills

• Has owned product analytics at a B2C software company - conversion funnels, feature adoption, retention, user segmentation
• Updated
• Deep understanding of subscription and mobile app metrics: trial conversion, trial-to-paid modeling, LTV, renewal rates, cohort analysis

Depth with data analytics and engineering tools (SQL, dbt, BigQuery, Python, Mixpanel, Amplitude, etc.)

Experience with mobile UA attribution — MMP (AppsFlyer, Adjust, or similar), SKAN, multi-touch

Practical experience building with AI/LLM tools

Soft skills: Effective communication: when they’re asked a question, they answer it succinctly and directly.

Traits to avoid

• Heavy data engineers or data scientists
• People working on B2B SaaS products or e-commerce
• VP level and above, or anyone who needs a big team