Data Analyst (Customer Service)
About the team
Salmon Customer Service is a team focused on making our customers’ lives easier across every product in the company. We build scalable support processes, shared standards, and tools that help customers solve their issues quickly and efficiently. Our goal is simple: remove friction, help people solve their tasks quickly, and create a service experience that truly feels wow.
CS Analytics is the data backbone of this layer. We own operational and historical reporting, data mart hygiene and DWH collaboration, request categorisation, workload analytics and staffing forecasting, end-to-end customer request journey analytics, and monitoring & alerting on top of all of it. Our work is what turns customer service into a measurable, manageable, continuously improving function — and the connective tissue between products, features, and operations.
Your Future Responsibilities Await:
Build end-to-end analytics of CS processes across customer requests.
Own core process metrics: repeated contacts, cost, full handling time, escalation rate, backlog, aging, SLA, and time in each stage.
Build dashboards, datasets, and reports that help CS leadership, team leads, Product, and Operations identify where the process breaks.
Translate business problems into analytical and technical requirements for better logging, CRM structure, and process design.
Step in beyond your scope when needed — we value ownership over rigid roles.
What we expect from the candidate:
2–3+ years of hands-on experience in data analytics.
Organized, reliable, and able to manage multiple priorities independently.
Strong SQL skills and analytical thinking.
Ability to document metric logic, assumptions, data sources, and limitations.
Strong English communication skills for working with both business and technical stakeholders.
Would be a big plus:
Degree in Computer Science, Engineering, Mathematics, Statistics, Data Science, Economics, or a related field.
Experience with operational, Customer Service (CS), CRM, or process analytics data.
Experience using Python or pandas for ad hoc analysis, validation, and data preparation.
Experience with statistical analysis is a plus, but not the main focus of the role.
Salmon Customer Service is a team focused on making our customers’ lives easier across every product in the company. We build scalable support processes, shared standards, and tools that help customers solve their issues quickly and efficiently. Our goal is simple: remove friction, help people solve their tasks quickly, and create a service experience that truly feels wow.
CS Analytics is the data backbone of this layer. We own operational and historical reporting, data mart hygiene and DWH collaboration, request categorisation, workload analytics and staffing forecasting, end-to-end customer request journey analytics, and monitoring & alerting on top of all of it. Our work is what turns customer service into a measurable, manageable, continuously improving function — and the connective tissue between products, features, and operations.
Your Future Responsibilities Await:
Build end-to-end analytics of CS processes across customer requests.
Own core process metrics: repeated contacts, cost, full handling time, escalation rate, backlog, aging, SLA, and time in each stage.
Build dashboards, datasets, and reports that help CS leadership, team leads, Product, and Operations identify where the process breaks.
Translate business problems into analytical and technical requirements for better logging, CRM structure, and process design.
Step in beyond your scope when needed — we value ownership over rigid roles.
What we expect from the candidate:
2–3+ years of hands-on experience in data analytics.
Organized, reliable, and able to manage multiple priorities independently.
Strong SQL skills and analytical thinking.
Ability to document metric logic, assumptions, data sources, and limitations.
Strong English communication skills for working with both business and technical stakeholders.
Would be a big plus:
Degree in Computer Science, Engineering, Mathematics, Statistics, Data Science, Economics, or a related field.
Experience with operational, Customer Service (CS), CRM, or process analytics data.
Experience using Python or pandas for ad hoc analysis, validation, and data preparation.
Experience with statistical analysis is a plus, but not the main focus of the role.