Develop knowledge and expertise in Ki’s business domains to generate insights and measurement on initiatives that drive company objectives.
Collaborate with business stakeholders to identify opportunities for leveraging data analytics to drive commercial results and improve operational efficiency.
Identify opportunities to leverage data analytics techniques to extract value from both internal and external data assets to enrich analytical capabilities.
Develop and maintain the core data sets underlying the suite of analytical tools used by the team
Create and maintain data visualizations and dashboards using tools such as Tableau, Power BI, or similar.
Develop scalable data solutions that conform to Ki’s technology and engineering principles and industry best practice.
Preserve the integrity of data, making sure it is accurate, consistent, and reliable throughout its lifecycle.
Investigate and lead timely resolution of emerging issues with underlying data systems and models as and when these arise.
Ensure that domain data is managed and used according to Ki’s data governance policy and best practice principles.
Ensure all data systems and models are documented in line with Ki wide standards
Recommend ways to improve data efficiency and reliability
Increase the degree of automation within the team’s data systems and tools
Investigate new tools that would help the team store, structure and analyse data.

Proficiency in SQL and Python to manipulate and analyse datasets
Experience with data reporting and visualisation tools (e.g. Tableau, Looker, Dash, Streamlit)
Solid understanding of statistical techniques (e.g. regression, clustering, correlation analysis), with ability to apply these to commercial problem solving.
Experience working in cloud native environments (especially GCP) would be plus.
Experience with designing and implementation of data structures to ensure ease of use and accessibility by a broader audience.
Self-organised, good at documenting and communicating findings and approach.
Excellent communicator, able to present complex analysis to both technical and non-technical audiences.
Experience working in a regulated industry

Data Analyst

Key skills