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Scentbird is a digital subscription service for fragrance lovers, offering access to over 1,000+ designer perfumes each month. The company operates multiple brands including Scentbird, Deck of Scarlet, Confessions Of A Rebel, Goodhabit, Sanctuary, and Drift.
The Senior Product Analyst will focus on quantitative understanding of user behavior within Scentbird, using digital footprints, surveys, and experiments to learn what users like, dislike, and what drives engagement, retention, and churn.
You will serve as a two-way driver: translating business goals into data requests, reports, and dashboards, while also proactively exploring data to surface insights and drive decisions.
Key Responsibilities:
- Roll out a 'data-as-a-service' approach for the Product team, making data accessible, understandable, and actionable
- Communicate with Product and cross-functional teams to define metrics, plan report structures, create visually appealing dashboards, and automate reporting in Looker
- Measure the impact of product features and growth experiments on key metrics (conversion rate, active subscriptions, customer lifetime value)
- Conduct ad hoc analysis to investigate data anomalies (usage spikes, conversion drops) and translate findings into actionable recommendations
- Build and maintain analytical tools and services, including LLM-powered automation, enabling the Product team to self-serve analytics
You will report to the Product Analytics Lead.
Desired Traits:
- Proactive: bring proposed approaches, not just problems; finish what you start
- Communicate opinions simply, backed by numbers
- Embrace new technologies and actively integrate them into your work, including AI tools
- Comfortable making mistakes and admitting knowledge gaps
Requirements:
Experience and Product Thinking:
- 3+ years of data analytics work experience
- Experience delivering analytical solutions for complex product tasks (user pattern research, experiment support, feature analysis, use-case analysis)
- Understanding of overall business value, not just numbers and charts
Statistics, Experimentation, and Causal Inference:
- Strong knowledge of statistical methods and quantitative analysis for decision-making
- Advanced A/B testing experience: designing, running, and analyzing complex experiments including variance reduction, sequential testing, multiple comparisons, sample ratio mismatch checks, and heterogeneous treatment effects
- Solid command of causal inference methods beyond A/B testing, with clear understanding of when each method's assumptions hold
Machine Learning:
- Hands-on experience applying machine learning to product problems (churn models, propensity models, uplift modeling, segmentation, recommendations)
- Ability to take models from analysis to working product features or decision processes
Data, Tools, and Engineering:
- Experience writing SQL queries and working with large datasets
- Experience with product analytics and BI tools (GA, Mixpanel, Amplitude, Looker, Tableau, or similar)
- Strong engineering habits in Python: building maintainable services and tools (packaged code, version control, tests, APIs, scheduled pipelines)
- Active use of LLMs to speed up coding and automate analytical workflows
Communication:
- High-level written and verbal communication skills
- English at upper-intermediate level or higher
Note: This role is for overseas application only; no domestic (U.S.) applications will be considered.
