Senior Insight Analyst Job Description Template
Our company is looking for a Senior Insight Analyst to join our team.
Responsibilities:
- Work on operational data and build dashboards to identify KPI’s;
- Perform customer/marketing analytics and also derive insights from data;
- Work cross-functionally with sales, marketing and finance teams;
- Responsible for quantifying costs and benefits associated to change programs and their integration into our resource plans;
- Segment customers and carry out analysis;
- Analyse campaigns and develop improvements for future ones;
- Work alongside senior stakeholders to provide actionable insight to improve business strategy;
- Develop and implement the analysis dashboards for key stakeholders using the provided tools and systems (R, R-Shiny);
- Use a confidence-based approach to make recommendations on how much benefit we can allocate against our budget assumptions;
- Proactively work with key agencies, partners and other third parties to support customer analysis requirements;
- Analysing overall company performance;
- Forecasting.
Requirements:
- Customer Analytics knowledge ideal;
- R needed for data manipulation and analysis to provide insight;
- Highly numerate with strong analytical & problem-solving skills;
- Experience of translating complex analysis and data into a simple story that is understandable, authoritative, digestible and compelling;
- Practical knowledge of how to use the latest analytical thinking in a commercial environment;
- Have experience of multiple insight tools including Alteryx, Power BI, Tableau, SQL or similar;
- Highly capable in using PowerPoint to communicate complex analysis simply & compellingly;
- Understanding of analysis techniques;
- Background in using data and insight to constructively challenge the status-quo and organisational myths;
- Comfortable working with executives; providing professional, accurate, and strategic advice;
- Skills to collaborate with and influence virtual teams to deliver change;
- Ideally experience performing customer analytics within a commercial environment;
- Ability to model in Python/R;
- A/B testing;
- SQL for data extraction and Power BI for dash boarding.