Product Data Scientist

2 days ago

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VoIP business phone service • hosted VoIP • Small business phone systems • web conferencing • virtual contact center

1001 - 5000

Description

• Define and track key performance indicators for our products. • Generate insights about how our users and customers use our platform to inform future product development and adoption growth. • Design, deliver and automate reports, oversee analytics tagging, master exploratory analysis and insight, all in close collaboration with partners across the product and business groups. • Partner with product managers on the end-to-end process of test design, implementation and analysis. • Document and communicate findings and insights to stakeholders. • Designing ETL data processing to provide stable reporting in a dynamic data environment. • Proactive trend analyses to surface underlying insights and bring forth early strategic discussion. • Engage in data deep dives and experiments, including hypothesis formulation, experimental design, significance-setting, and post-experiment analysis. • Identify and interpret trends and/or patterns within complex data sets. • Responsible for data analysis, validation, cleansing, collection, and reporting. • Analyze and maintain reports and dashboards to generate timely actionable insights.

Requirements

• 3+ years of experience as a product data analyst or similar role. • Bachelor's degree in an analytical field such as economics, mathematics, or computer science is a plus, but not required. • Experience with product analytics tools such as Amplitude, Mixpanel, GA4 or similar. • Strong understanding of event-driven analytics and ability to craft complex tracking plans for behavioural and KPI measurement, both at front-end and back-end level are a must. • Knowledge of user segmentation, and consumer insights experience. • Experience with data visualisation tools like Tableau, Looker, Looker Studio or similar is a strong plus. • Experience working on ETL and Data Modelling. • SQL is a must - you will be responsible for extracting data through queries (Python is a plus, but not mandatory). • Deep understanding of subscription metrics such as Churn rate, MRR, ARR, ARPU. • Proven ability to drive business results with their data-driven insights. • High level of initiative and a ‘make it work’ ethos. • Excellent verbal and written communication skills.