Product Data Analyst

The Role

We're seeking a Product Data Analyst to join our mission-driven team and help shape the future of online safety technology. You'll play a crucial role in analysing user behaviour, product performance, and safety metrics to drive data-informed decisions that enhance our verification technologies and improve user experiences while maintaining the highest safety standards.

What You'll Work On

Product Analytics & Insights

• Analyse user journeys across our age verification and content moderation platforms to identify friction points and optimisation opportunities
• Track and report on key product metrics including verification success rates, completion times, false positive/negative rates, and user drop-off patterns
• Conduct cohort analysis and user segmentation to understand behaviour patterns across different demographics and use cases
• Develop dashboards and automated reporting for product teams to monitor real-time performance of verification workflows

Platform Observability & Performance

• Design and implement observability frameworks to monitor platform health, API performance, and system reliability
• Create and maintain monitoring dashboards for infrastructure metrics, application performance, and user experience indicators
• Analyse system logs and performance data from NoSQL databases to identify bottlenecks and optimisation opportunities
• Collaborate with DevOps and Engineering teams to establish SLA monitoring and alerting for critical verification services
• Track and report on platform uptime, response times, and scalability metrics across our global infrastructure

Safety & Compliance Analytics

• Monitor and analyse safety metrics related to child protection and age verification accuracy
• Investigate anomalies in verification patterns that could indicate fraudulent activity or system vulnerabilities
• Support compliance reporting by analysing age assurance effectiveness and regulatory adherence metrics
• Collaborate with ML teams to evaluate model performance and bias detection in age estimation algorithms

Business Intelligence & Strategy

• Partner with Product Managers to define success metrics for new features and conduct A/B testing analysis
• Analyse client onboarding data and usage patterns to inform product roadmap decisions
• Conduct competitive analysis and market research to identify opportunities for product enhancement
• Support sales and customer success teams with data-driven insights on platform performance and ROI

Data Infrastructure & NoSQL Management

• Work with NoSQL databases (MongoDB, Elasticsearch, etc.) to extract insights from unstructured verification and content moderation data
• Ensure data quality and integrity across all verification and moderation systems, including document stores and time-series databases
• Develop and maintain data models that support product analytics and business intelligence needs across both SQL and NoSQL environments
• Create documentation and best practices for data analysis within the product organisation
• Optimise NoSQL query performance and data retrieval patterns for analytics workloads

What We're Looking For

• Bachelor's degree in Data Science, Statistics, Mathematics, Economics, or related quantitative field
• 3+ years of experience in product analytics, preferably in B2B SaaS, RegTech, or online safety/security sectors
• Proficiency in SQL and NoSQL databases (MongoDB, Elasticsearch, DynamoDB, or similar)
• Experience with data visualisation tools (Tableau, Power BI, or similar) and observability platforms (Grafana, DataDog, New Relic)
• Experience with statistical analysis and A/B testing methodologies
• Strong Python or R skills for data analysis and modelling
• Understanding of API analytics, platform monitoring, and ability to work with large, complex datasets
• Experience with system observability, performance monitoring, and infrastructure metrics analysis

Nice to have

• Experience in online safety, age verification, content moderation, or compliance technology
• Knowledge of machine learning concepts and model evaluation metrics
• Familiarity with privacy-preserving analytics techniques and GDPR compliance
• Experience with cloud analytics platforms (AWS, GCP, or Azure) and their monitoring services
• Understanding of biometric and identity verification systems
• Background in fraud detection or anomaly detection analytics
• Experience with time-series databases and real-time streaming analytics
• Knowledge of containerised environments (Docker, Kubernetes) and microservices observability

Technical Skills

• Analytics Tools: SQL, NoSQL (MongoDB, Elasticsearch, DynamoDB), Python/R, Excel, statistical analysis packages
• Visualisation & Monitoring: Tableau, Power BI, Grafana, DataDog, New Relic, or similar BI and observability tools
• Data Platforms: Experience with cloud data warehouses, ETL processes, and real-time data streaming
• Testing: A/B testing frameworks and statistical significance testing
• AI/ML: Understanding of model evaluation, bias detection, and performance metrics
• Platform Observability: System monitoring, performance analysis, log aggregation, and infrastructure metrics
• Database Technologies: Proficiency in both relational and document-based database analytics

Technical Stack

• Languages: Go, Python,
• Package Managers: NPM, Yarn, PNPM
• Cloud: Google Cloud Platform (GCP)
• Infrastructure: Docker, Kubernetes, Rancher, Jenkins CI/CD
• CDN & Edge: Cloudflare
• Monitoring & Analytics: Grafana, Metabase
• AI/ML Development: Claude Code, Cursor IDE, Gemma models
• Development Tools: Various specialised build environments for analytics, cloud functions, and automation.