As a Data Analyst on the Customer Experience Team, you will play a crucial role in analysing large datasets to uncover actionable insights that will drive improvements in customer satisfaction, retention, and overall experience. You will collaborate closely with cross-functional teams including customer care, marketing, digital & product to identify opportunities for optimisation and develop data-driven solutions.

Key Responsibilities:

1. Ability to extract data from and have an understanding of how databases work.
2. Have the ability to identify discrepancies in data
3. Capable of collecting, managing, and converting raw data into usable information for interpretation.
4. Conduct exploratory data analysis on large datasets (Teradata, Brio) to identify trends, patterns, and correlations related to customer behaviour and satisfaction.
5. Utilize advanced statistical techniques to segment customers based on their preferences, needs, and behaviours.
6. Collaborate with stakeholders to design and implement experiments to test hypotheses and evaluate the impact of strategic initiatives on customer experience metrics.
7. Ability to connect experience data (Qualtrics/Medalia) with operational data to deliver insights. 
8. Conduct diagnostic analysis to answer the question “why did something happen?” by working with other related data sources, including past data, to reveal more insights into current trends.
9. Create data visualizations and reports to communicate findings and insights to both technical and non-technical stakeholders.
10. Work closely with the engineering team to develop a predictive AI model to forecast customer behaviour, churn, and lifetime value, enabling proactive strategies for customer retention and engagement.
11. Continuously evaluate and improve data quality and integrity to ensure the accuracy and reliability of analyses and models.
12. Stay up to date with the latest trends and advancements in data science and customer experience domains, and proactively identify opportunities for innovation.

Qualifications:

Technical Skills:

1. SQL and NoSQL: Proficiency in database management and querying languages.
2. Spreadsheets: Ability to use tools like Microsoft Excel for data manipulation and presentation.
3. Data Visualization Tools: Familiarity with Tableau or Power BI to create compelling data visualizations.
4. Database management: Ensuring data quality and readiness for analysis.
5. Quantitative Analysis: Strong foundation in statistical methods and predictive modelling.

Soft Skills:

1. Analytical Thinking: Ability to interpret complex data and draw conclusions.
2. Problem-Solving: Identifying issues and proposing effective solutions.
3. Communication: Comprehend the ‘ask’ and clearly articulate findings to stakeholders.
4. Collaboration: Working with different departments to gather and share insights.
5. Customer-Centric Approach: Understanding customer needs and behaviours through data.
6. Domain Knowledge: Familiarity with the industry and market trends.