About the company
Scentbird — подписка на пробники дизайнерского парфюма. стартап прошел Y Combinator в 2015 году.
Размер команды — 51-200 | Инвестиции — $29M
PLEASE NOTE THIS ROLE IS FOR OVERSEAS APPLICATION, NON -U.S. ONLY. NO DOMESTIC (U.S.) APPLICATIONS WILL BE CONSIDERED.
The Senior Product Analyst focuses on a quantitative understanding of what users do within Scentbird, based on digital footprints, surveys and experiments. The aim is to learn what users like or dislike and what leads them to engage, return or churn.
We see the Senior Product Analyst as a two-way driver: they turn business goals into data requests, reports and dashboards, and they proactively explore data to bring insights and drive the right decisions.
The Senior Product Analyst reports to the Product Analytics Lead.
Responsibilities
- Rolling out a ‘data-as-a-service’ approach for the Product team to make data easy to access, understand and use for decisions
- Communicating with Product and cross-functional teams: defining the metrics they track, planning report structures, making reports visually appealing and easy to understand, and automating reporting in our BI system (we use Looker)
- Measuring the impact of existing and new product features and growth experiments on our key metrics (e.g., conversion rate, number of active subscriptions, customer lifetime value)
- Doing ad hoc analysis: if something emerges in the data, like a spike in usage or a drop in conversions, you have to find out “why?”. Reports and research should not come just as numbers and distributions, but as action items (e.g., to increase X, we have to do Y)
- Building and maintaining analytical tools and services, including LLM-powered automation, that let the Product team answer questions without waiting on an analyst
Requirements
- Experience and product thinking
- 3+ years of data analytics work experience
- Experience delivering analytical solutions for complex product-related tasks (user pattern research, supporting experiments, feature analysis to improve product metrics, use-case analysis, etc.)
- Understanding of overall business value, rather than caring only about numbers and charts
- Statistics, experimentation and causal inference
- Strong knowledge of statistical methods and of using quantitative analysis to impact key decisions
- 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 a clear understanding of when each method’s assumptions hold
- Machine learning
- Hands-on experience applying machine learning to product problems, such as churn and propensity models, uplift modeling, segmentation, or recommendations, and taking a model from analysis to a working part of a product or decision process
- Data, tools and engineering
- Experience writing SQL queries and working with large data sets
- Experience with product analytics and BI tools (e.g., GA, Mixpanel, Amplitude, Looker, Tableau, or similar)
- Strong engineering habits in Python: building maintainable services and tools rather than one-off scripts (packaged code, version control, tests, APIs, scheduled pipelines), and actively using LLMs to speed up coding and to automate analytical workflows
- Communication
- High-level written and verbal communication skills
- English at upper-intermediate level or higher
Conditions
- Competitive base compensation
- Bonus program
- Remote first
- Paid time off
- A fun, creative and energetic work environment