Analytics Manager - Business Analytics London

As an Analytics Manager, you will drive analytics for our commercial operations, partnering closely with Revenue Operations and Strategic Finance, and other business operations teams. You will lead a team of Analytics Engineers and Data Scientists, managing the end-to-end delivery of analytics solutions, from data infrastructure to predictive models and actionable insights. You will play a key role in improving financial and operational performance, by defining success metrics and identifying opportunities for optimization.

Data Analytics is a critical function that directly influences our strategic decisions and business outcomes. As a leader within this department, you will have a strong support network of Analytics Engineers, Data Scientists, and very collaborative business stakeholders.

How you'll make impact:

You will manage a team of Analytics Engineers and Data Scientists that designs, builds, and maintains data pipelines, develops predictive models, and delivers self-serve analytics tools and dashboards.

You will be responsible for delivering analytics solutions that improve financial and operational performance across our commercial teams. This includes scoping projects, managing delivery, mentoring team members, and providing impactful insights.

Contribute to strategic planning and decision-making by providing data-driven recommendations and identifying high-impact areas for improvement.

Ensure the collection and modeling of accurate and relevant data to generate meaningful business insights.

Enhance the data maturity of our commercial operations by promoting data-driven decision-making.

Partner with Revenue Operations, Strategic Finance, and other Business Operations teams to build data analytics solutions.

Qualifications

Experience in delivering data warehouses, self-serve analytics tools, and data products/insights that drive business value.

Experience managing and supporting high performing teams, as well as managing project delivery and planning.

Demonstrable experience in building measurement frameworks and using quantitative methods (including predictive modeling and statistical analysis) to validate results.

Strong experience building analytics with cloud data warehouses, Google BigQuery, Snowflake, modern data stack technologies like DBT, Fivetran, Airflow.

Demonstrable experience in partnering with various stakeholders and building data products that support many technical and non-technical users.

Experience in cross-functional collaboration with stakeholders, including setting expectations, prioritizing projects, and scoping analytical deliverables.

Strong analytics skills, including proficiency in SQL and Python, data modeling and engineering, applied statistics (e.g., hypothesis testing, regression analysis), and hands-on experience with BI tools (e.g., Tableau, Power BI, Looker).

Experience with financial modeling and forecasting, preferably within high-growth SaaS environment.