Head of Data Analytics
$120,000 - $180,000
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Posted 8 days ago
SENIORITY
Manager
SALARY
$120,000 - $180,000
About the role
- The Head of Data & Analytics will be accountable for:1. Driving Product & Growth Intelligence
- Develop a deep understanding of user behavior across the product ecosystem
- Identify key activation, engagement, retention, and monetization drivers
- Help establish product as the primary growth engine2. Building a Product-Led Analytics Function
- Create scalable reporting and analytics frameworks across Product, Growth, and Marketing
- Develop KPI frameworks tied to company-wide objectives
- Build visibility into behavioral funnels, cohort performance, and user lifecycle metrics3. Identifying Growth & Retention Opportunities
- Proactively surface insights and recommendations to leadership
- Identify growth levers that improve:
- WAU/MAUActivationFreemium conversion
- RetentionInvite loops and virality4. Supporting Product-Market Fit Discovery
- Analyze user behavior across core personas
- Help the organization understand where engagement is strongest and where friction exists5. Developing Executive & Board-Level Reporting
- Build and maintain executive dashboards and KPI visibility
- Support monthly and quarterly Board reporting
- Translate complex data into clear business narratives and actionable recommendations6. Establishing a Data-Driven Culture
- Help evolve Photobucket into a truly data-informed and product-led organization
- Create consistency around metrics, reporting, and business intelligence
- Partner cross-functionally to improve decision-making velocity and accountability
- What you will bring to Photobucket
- Required 10+ years of experience in analytics, product analytics, marketing analytics, or business intelligenceB2C SaaS product analytics experience
- Product-led growth experience
- Technical Fluency: Strong SQL skills and comfort working with large, complex datasets. Fluency with BI tools (Amazon Quick, Tableau, Power BI, or similar) and modern data stacks (Snowflake, AWS database tools, or similar)
- Familiarity with AWS data pipelines (Glue, Kinesis, S3-based data lakes)
- Proficiency in Python or R for statistical modeling and analysis
- Strong foundation in A/B testing, statistical significance, and cohort analysis
- Ability to build and maintain analytical data models independently
- Fluency with AI-assisted analytics and LLM-based insight discovery
- Strong executive communication, ability to translate Ability to translate complex data into clear executive narratives and business recommendations
- Consumer engagement platforms
- Freemium business models
- Social, media, or network-effect products
- Deep understanding of:
- Behavioral analytics
- Retention analysis
- Funnel optimization
- Cohort analysis
- Product experimentation
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
