Apply📍 United Kingdom
🧭 Full-Time
💸 42000.0 - 50000.0 GBP per year
🔍 SaaS
- A Bachelor’s Degree in Data Analytics, Statistics, Computer Science, or a related field.
- Minimum of 4 years experience in a data analysis or similar role, preferably within a fast-paced SaaS or technology environment.
- Proficiency in data analysis tools and languages, such as Python, R or similar for advanced data manipulation and analysis.
- Understanding of the data pipeline, with familiarity with ETL processes.
- Familiarity with statistical analysis techniques e.g., regression, hypothesis testing.
- Experience working with large datasets and deriving actionable insights.
- Proficient in Lucene query syntax for querying and analyzing data in OpenSearch.
- Strong SQL skills for working with AWS Quicksight to create reports and visualizations.
- Advanced Excel capabilities for quick data manipulation and supplementary analysis.
- Experience working with Google Analytics for user behavior tracking and performance metrics.
- Familiarity with Hotjar for heatmaps and user interaction insights.
- Ability to define and monitor product KPIs and OKRs.
- Effective communication and interpersonal skills to work collaboratively and present findings.
- Collect, clean, and analyze data from various sources to identify trends and insights.
- Collaborate with departments, including Sales, Marketing, Product, Engineering, and Client Success, to understand their data needs and provide tailored insights.
- Provide statistical analysis to validate experiment results and recommend next steps.
- Ensure data integrity by regularly auditing and maintaining data cleanliness within systems like CRMs and marketing platforms.
- Partner with the Client Success team to identify and track key metrics driving client satisfaction and retention.
- Develop models to predict churn and identify at-risk users.
- Provide training and tools for teams to access and utilize data effectively.
- Build and maintain dashboards for real-time monitoring of these metrics.
- Interpret data and generate actionable recommendations for the team.
- Analyze client behavior to understand engagement patterns, activation rates, and drop-off points.
PythonSQLETLGoogle AnalyticsData visualization
Posted 23 days ago
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