Five ways to build a gender-diverse team

1. Start collecting data (if you aren’t already)

Can you tell I’m a data scientist? Data is the best way to objectively measure what your team’s gender diversity actually  looks like. This will help you to quantify where you are now vs. where you want to be, and see if gender diversity is heading in the right direction. Here are some questions to get you started:

• What is the gender split in your current team? How has that changed over time? Are things improving, staying the same or getting worse?
• Are there any key differences in salary/seniority/types of role by gender?
• Does the attrition in your team vary by gender?
• What is the gender split of applicants by role? How does this change throughout the recruitment process?
• What proportion of interviews have a gender-diverse interview panel? How does this impact the outcome for the candidate?

2. Make diversity a team priority

Your team’s metrics of success should include a goal for gender diversity that is equally as important as your other objectives. At Peak, we have the bold target of 50% female employees by 2025. An increase from 26% to 33% of female data scientists by the end of 2021 would mean we’re on track to achieve our 2025 goal.

This has been communicated to the whole team alongside other objectives – creating the momentum we needed as we’ve recently hit our 33% goal! We also mention diversity as early on as we can in the recruitment process and in our job ads, in order to make sure that we’re attracting people who believe it’s an important cause, too.

Are you part of a team with no clear diversity goals? Lead by example. Define these goals, start a Diversity & Inclusivity committee and create a roadmap for the next year for well-defined initiatives you believe will be impactful.

3. Create more opportunities for women

By looking at the skills and experience of women in your team, you can evaluate whether you’re offering opportunities that will attract women. Analyzing which subjects your team have studied and to what level is a great place to start.

38% of women in our data science team have PhDs vs. 57% men, meaning opportunities that are relevant for students finishing BScs and MScs could have a positive impact on gender diversity. We have introduced a graduate scheme this year and four of the eight successful candidates are women and have supervised five MSc students with their dissertations, three of which have been offered full-time roles. Subject area is also important; a higher proportion of women in our team have come from a mathematics and statistics background vs. physics or computer science, so we’ve focused on building connections with and taking part in career events for mathematics departments.

Research by the Alan Turing Institute shows that women are more likely than men to be in analytics roles vs. alternatives such as data engineering, architecture or development. Creating specialist roles within teams can be a great way to scale a team anyway, so increasing diversity is an added bonus! We have an Insight team (which currently has a 50/50 gender split) that we advertise using a different job description than when we’re recruiting for data scientists.

We currently have 33% female data scientists, but this would be 26% if people in the roles mentioned above hadn’t joined the team. This goes to show that reviewing the opportunities you offer can be hugely worthwhile! We still have work to do on improving the diversity of our R&D team, which will be a huge focus for us next year.

4. Create an open culture that listens to feedback

There are two approaches to this that are both important; (1) building trusting and open relationships and (2) regularly collecting widespread feedback that you can analyze by gender.

It’s crucial that managers can be allies for women in your team. Both formal and informal training for managers can be helpful. As an example, our Data Science Management team read and discussed topics from ‘Invisible Women’ by Caroline Criado Perez, relating it to experiences data scientists in the team may have. You can also set up regular catch ups for women in your team, where they can openly discuss the challenges they face with others that can directly relate. This is less about problem solving, and more about making sure women in the team feel valued, empowered and included.

Having an accurate gauge of how your team feels and a consistent mechanism for feedback is helpful for a lot of reasons. Surveys can be a very useful tool for this, especially as you can include a combination of quantitative and qualitative questions. Consider getting feedback on the following areas on a regular basis… and most importantly, make sure you look at the differences by gender:

• The recruitment process: We improved the diversity of our panels after feedback that someone found a completely male panel uncomfortable
• Team or company policies: We created a new maternity leave policy after feedback from women that it may affect their likelihood of staying at Peak
• Overall job satisfaction and stress: Women, on average, have more care responsibilities, so may feel more stressed or burnt out

5. Remember to give back

Having diversity goals as a company and team is important, not only to provide a shared goal, but also to make businesses accountable for change. You may create an amazing team that is great at hiring diverse talent, but if you’re hiring all of the diverse talent without creating more, you’re not contributing to longer term change.

A few ideas on how you can give back are:

• Set up external mentoring schemes: As well as helping people get into the data science industry, it’s a great development opportunity for people in your team
• Be involved with data science communities: There are events targeted at women too, such as Her+Data, which is a great way to support the great work other women are doing in the industry. It’s also a great chance to build your own network and profile!
• Outreach to universities and schools: Inspire the next generation of data scientists! Speak to them about all of the exciting problems you work on and be a role model.

To conclude, this blog post focuses on how collecting data, setting and communicating diversity goals, building a feedback culture, creating more opportunities and giving back can help you to build a diverse team, with a specific focus on gender. However, it’s important to remember that diversity is not limited to gender and this approach can (and should) be applied to other characteristics, too. 

Thank you for joining me on this mission to improve gender diversity within data science teams and I hope this has given you some inspiration!