Wellcome’s gender and ethnicity pay gaps

Gender pay gap is the difference between the average hourly rates of pay for men and women. Ethnicity pay gap is the difference between the average hourly rates of pay for people from racially minoritised groups and white people.

Comparing average rates of pay reflects broad trends in employment and salaries.

Wellcome’s data team carried out the analysis of our 2025 pay gap data. This was the first time we completed the full evaluation internally and allows more detailed exploration.

On 5 April 2025, Wellcome had a gender gap in median pay of 13.3%. While smaller than last year, this is slightly wider than the UK average, reported as 12.8% in 2025 by the Office for National Statistics (ONS). Our gender gap in mean pay was 23%.

Our gender pay gap is mostly a result of three factors:

• the proportion of employees who are men is lower at more junior job levels
• women are more likely to work in teams that have lower market-rate salaries
• mid-career progression slows for women

Over the past five years, our median gender pay gap has stayed between 13% and 16%. Year-on-year variations have mostly reflected the gender split of people joining Wellcome at different job levels.

This trend is similar among other UK organisations and in ONS data, meaning we need to do more to address structural and systemic drivers of our gender pay gap.

On 5 April 2025, Wellcome had an ethnicity gap in median pay of 5.1%. Our ethnicity gap in mean pay was 8.3%.

Our ethnicity pay gaps are a result of low representation of people from racially minoritised groups at more senior levels. The decrease in mean pay gap this year was driven mostly by the balance of new joiners at a senior level.

Interpretation should be tentative because Wellcome has not received ethnicity data from around 10% of our employees. This is a significant proportion of the workforce, whose data could affect the pay gap calculations considerably.

In 2025, we have:

• brought analysis of pay gap data in-house, enabling deeper integration with other data and department-level analysis and action
• continued training on equity, diversity and inclusion, which 98.5% of staff have completed
• used regular staff surveys to better understand employee experiences
• introduced an Equity Framework to clarify the relationship between science, health and equity across the organisation and all of our work, internally and externally

Next steps include:

• building diversity data dashboards for each member of our Executive Committee and setting local action plans due to the breadth of trends and needs across our departments
• understanding how the gender balance of shortlists relates to labour markets so that we can consider targeted actions
• enhancing support for colleagues returning from extended leave, including but not limited to child leave
• promoting our child leave policy more clearly
• continuing to focus during recruitment on diversifying teams, and ensuring inclusive practice is followed
• monitoring and analysing internal movement data to identify trends and mitigate bias in decision making