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.

Deliverables

Data collection and event tracking specifications aligned with product design.

Analysis and experiment plans covering methodology, parameters, phases, and effort estimation.

Insight reports, dashboards, and experiment readouts with clear recommendations and regular stakeholder updates.

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.

Full-time