Data Insight Analyst
- Translate business needs into measurable outcomes – Partner with stakeholders across the business, particularly in commercial and sales teams, to define clear, measurable KPIs that align with company goals, enabling us to track and optimize performance.
- Deliver impactful insights – Use a mix of self-serve reporting, exploratory analysis, and deep-dive investigations (i.e. conversion analysis, correlation analysis, cohort analysis) to uncover actionable insights that enhance commercial performance and influence strategic decisions.
- Identify opportunities and risks – Proactively explore key areas of opportunity or concern, diagnose analytics needs across the business, and identify where data-driven insights can deliver the greatest impact.
- Collaborate for optimal outcomes – Work closely with product analysts, data scientists, analytics engineers, and data engineers to design effective analytics solutions and deliver maximum business value.
- Think creatively and strategically – Bring curiosity, creativity, and a problem-solving mindset to explore new ways data can fuel growth and innovation.
- Mentor and support junior analysts – Share knowledge, provide guidance, and help develop analytical and storytelling skills across the team, fostering a culture of learning and excellence.
- Strong technical skills in analytics – Proficient in SQL and experienced working with modern data warehouses such as BigQuery, Snowflake, or Redshift.
- Experience delivering analytics solutions – Skilled in building and presenting insights using BI and visualization tools such as Looker, Tableau, or Power BI.
- Excellent communication and storytelling skills – Able to translate complex data into clear narratives and actionable recommendations for a range of stakeholders.
- Curiosity and an impact-driven mindset – Comfortable exploring ambiguity, identifying opportunities, and using data to solve meaningful business challenges.
- Ownership and collaboration – Confident managing projects independently while building strong relationships and aligning with stakeholders.
- Experience with Python or R – For exploratory data analysis, or statistical modeling.
- Familiarity with version control tools – Such as Git, to collaborate effectively in a modern analytics environment.
- Experience with dbt (Data Build Tool) – For building, testing, and maintaining reliable data models and transformations.
- Exposure to experimentation or forecasting – Understanding A/B testing, conversion analysis, or forecasting methods that inform strategic decision-making.
- Awareness of data best practices – Including data quality, documentation, and reproducibility within an analytics engineering context.
- You’re curious. You have a real desire to learn and create.
- You’re relentless. You keep going even when it’s easier not to.
- You’re customer-obsessed. You know how important customers are to what you do.
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