Overview:
The Senior Data Analyst drives product research, development, and data quality monitoring in a fast-moving SaaS environment, focusing on product and customer behavioural analysis to translate user data into actionable insights that shape product strategy. Working with rich, multi-signal datasets, the role cuts through noise to uncover opportunities for product optimization, evaluate feature performance, and explain how customers engage across their lifecycle. The ideal candidate has a passion for surfacing meaningful signals from broad, complex data and partnering with stakeholders to improve business outcomes.
Responsibilities
- Lead end-to-end product analyses: frame business questions, wrangle data, apply appropriate analytical methods, and communicate findings clearly to non-technical audiences.
- Partner with stakeholders to evaluate product design, feature adoption, and customer engagement, translating insights into actionable business solutions.
- Identify patterns and opportunities in rich, multi-signal datasets through exploratory analysis to support decision-making.
- Design, execute, and interpret A/B tests and experiments to validate product hypotheses and assess user behaviour impact.
- Monitor key product and customer metrics (activation, retention, conversion, churn) to detect anomalies and proactively surface insights.
- Own tracking quality: review event tracking specifications, perform QA, and safeguard data credibility, reliability, and privacy compliance.
- Support agile delivery by participating in sprint planning, helping prioritize features, and evaluating post-launch success.
- Enable self-service by serving ad hoc requests and building dashboards; continuously evaluate new data sources and improve data quality processes.
Requirements
- Bachelor's degree or above in Computer Science, Statistics, Management Information Systems, or related fields.
- Minimum 4 years experience in product or behavioural data analysis, ideally within SaaS or digital product environments.
- Strong hands-on SQL skills (SQL Server, Oracle, MySQL, or similar) and proficiency in Python or R for processing data and surfacing insights from rich, multi-signal datasets.
- Working knowledge of product analytics tools (e.g. Amplitude, Mixpanel, Google Analytics), including instrumenting and validating event tracking.
- Solid foundation in statistics, A/B testing, and experimentation design applied to product decisions.
- Strong problem-solving skills across the customer lifecycle (acquisition, activation, engagement, retention, monetization), with proven data cleaning and validation discipline.
- Sound business judgment to identify commercially impactful insights, paired with curiosity and persistence to carry original analysis through to outcome.
- Excellent organizational skills with attention to detail and a focus on quality and innovation.
- Strong interpersonal skills and excellent written and verbal English communication for cross-team collaboration.
- Eagerness to learn on the fly and master new tools and trends.
