Requirements
- Proven track record in analytics, strategy, or data roles in high‑growth, data‑rich environments
- Strong track record of personally delivering complex, high‑impact analysis (not just managing teams)
- Solid background of data governance and reconciliation, with a strong grasp of financial and e‑commerce metrics
- Comfortable operating as a senior individual contributor and team leader simultaneously
- Strong data management skills, having experience with Python / R and advanced SQL skills
- Excellent communication, presentation, and business partnering skills, inspiring confidence through powerful messaging and a natural rapport
- Comfortable with ambiguity, possessing the ability to proactively work independently and collaboratively
- Strong commercial acumen — able to connect analysis to revenue, margin and customer outcomes
- Outstanding organisational and time‑management skills, with a keen eye for detail when appropriate
- Resilient, pragmatic, and agile. Confident in making candid observations and openly engaging with difficult truths in order to deliver solutions
- Strong stakeholder management and collaboration skills to understand business needs, challenges and objectives
What the job involves
- The Head of Analytics is responsible for maximising the impact of analytics across HeliosX during a period of transition.
- The role will drive higher‑quality, insight‑led decision‑making by leveraging existing data capabilities and embedding advanced analytical thinking across the business. Operating as a hands‑on leader, the role combines direct delivery of high‑impact analysis with the development and uplift of analytics capability across the team, ensuring consistent, value‑driven outputs aligned to business priorities.
- Commercial Analysis and Insights
- Act as the lead analytical problem solver on the most critical business questions.
- Deliver end‑to‑end, deep‑dive analysis across areas such as:
- Acquisition performance & channel efficiency
- Retention, churn and LTV dynamics
- Pricing and commercial optimisation
- Operational performance and cost drivers
- Provide actionable recommendations based on data insights to inform strategic and operational decisions.
- Work with cross‑functional leadership to identify, collect, analyse, and interpret data to help refine and prioritise Group strategy.
- Move beyond descriptive reporting to diagnose root causes and identify clear actions.
- Work directly with senior stakeholders to shape decisions in real time.
- Lead the delivery of reports and presentations to communicate findings.
- Work with the Financial Planning & Analysis (FP&A) lead to ensure analytical insights are incorporated into the business plan and that variances to plan can be explained.
- Partner with Data Science to integrate predictive modelling, experimentation and advanced segmentation.
- Data Visualisation and Reporting
- Reduce time spent on manual reporting and dashboard production.
- Leverage AI and Snowflake capabilities to automate or eliminate low‑value workflows.
- Redefine team priorities toward fewer, higher‑impact analytical outputs.
- Establish a culture of proactive, hypothesis‑led analysis.
- Lead on BI education and data literacy for business stakeholders across functional teams.
- Ensure data‑driven insights are presented in a clear and actionable format.
- Team Management
- Set a new standard for problem structuring, analytical depth and commercial insight.
- Coach analysts through real work and live problem solving.
- Stay close to the work, actively reviewing and contributing to analysis.
- Introduce more rigorous approaches to hypothesis‑driven analysis, causal thinking and how to translate data into decisions.
- Work alongside Data Governance to improve metric clarity and trust over time.
Requirements
- Proven track record in analytics, strategy, or data roles in high‑growth, data‑rich environments
- Strong track record of personally delivering complex, high‑impact analysis (not just managing teams)
- Solid background of data governance and reconciliation, with a strong grasp of financial and e‑commerce metrics
- Comfortable operating as a senior individual contributor and team leader simultaneously
- Strong data management skills, having experience with Python / R and advanced SQL skills
- Excellent communication, presentation, and business partnering skills, inspiring confidence through powerful messaging and a natural rapport
- Comfortable with ambiguity, possessing the ability to proactively work independently and collaboratively
- Strong commercial acumen — able to connect analysis to revenue, margin and customer outcomes
- Outstanding organisational and time‑management skills, with a keen eye for detail when appropriate
- Resilient, pragmatic, and agile. Confident in making candid observations and openly engaging with difficult truths in order to deliver solutions
- Strong stakeholder management and collaboration skills to understand business needs, challenges and objectives
What the job involves
- The Head of Analytics is responsible for maximising the impact of analytics across HeliosX during a period of transition.
- The role will drive higher‑quality, insight‑led decision‑making by leveraging existing data capabilities and embedding advanced analytical thinking across the business. Operating as a hands‑on leader, the role combines direct delivery of high‑impact analysis with the development and uplift of analytics capability across the team, ensuring consistent, value‑driven outputs aligned to business priorities.
- Commercial Analysis and Insights
- Act as the lead analytical problem solver on the most critical business questions.
- Deliver end‑to‑end, deep‑dive analysis across areas such as:
- Acquisition performance & channel efficiency
- Retention, churn and LTV dynamics
- Pricing and commercial optimisation
- Operational performance and cost drivers
- Provide actionable recommendations based on data insights to inform strategic and operational decisions.
- Work with cross‑functional leadership to identify, collect, analyse, and interpret data to help refine and prioritise Group strategy.
- Move beyond descriptive reporting to diagnose root causes and identify clear actions.
- Work directly with senior stakeholders to shape decisions in real time.
- Lead the delivery of reports and presentations to communicate findings.
- Work with the Financial Planning & Analysis (FP&A) lead to ensure analytical insights are incorporated into the business plan and that variances to plan can be explained.
- Partner with Data Science to integrate predictive modelling, experimentation and advanced segmentation.
- Data Visualisation and Reporting
- Reduce time spent on manual reporting and dashboard production.
- Leverage AI and Snowflake capabilities to automate or eliminate low‑value workflows.
- Redefine team priorities toward fewer, higher‑impact analytical outputs.
- Establish a culture of proactive, hypothesis‑led analysis.
- Lead on BI education and data literacy for business stakeholders across functional teams.
- Ensure data‑driven insights are presented in a clear and actionable format.
- Team Management
- Set a new standard for problem structuring, analytical depth and commercial insight.
- Coach analysts through real work and live problem solving.
- Stay close to the work, actively reviewing and contributing to analysis.
- Introduce more rigorous approaches to hypothesis‑driven analysis, causal thinking and how to translate data into decisions.
- Work alongside Data Governance to improve metric clarity and trust over time.
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