Improving diversity in data and analytics teams

Sandra Namatovu our consultant managing the role
Posting date: 6/5/2013 11:01 AM

We are a data-driven world fueled by information. Whether it's the obvious players such as the financial or retail industries or the not so obvious from sports to music; everyone uses data within their business to make decisions. That is the heart of business intelligence (BI). BI helps businesses identify, discover, and analyse data from revenue, costs, incomes, and products or services. 

If you google "data science" or "data scientist", you might get what schools offer degrees in the field, where to find a job, or you might find articles which talk about the profession as whole; "the hottest job of the 21st century" or "data scientists are the rock stars of the techworld". Yet, across the Google pages and throughout the articles you might notice a troubling trend; there remains a shortage of data science professionals in both the US and the UK. Why?

Diversity in Data

Though the percentage of women in the STEM and technology fields has declined since the early 90s when it peaked at 36%. Yet, the shortage remains. It's not just women, however, who are underrepresented. Other minorities are underrepresented as well. 

With around 12% of Hispanic/Latino or African-American Data Science enrollees and 35% women enrolled in technical education fields, it would seem a bit of fostering and encouragement might generate further interest in the field. But, to remember when building your diverse data team, everyone wants simply to be treated as equal - to have their thoughts and voice heard.

According to a recent article in Forbes, women in the US hold 26% of data jobs. The number drops to half that in the UK. And the numbers continue drop in regard to diverse representation in the field. Proposed reasons for the gap are a lack of education in the STEM fields early on, a lack of mentorship for women in data science, even resources and rules stemming from human resource departments. In other words, companies need to be educated on the benefits of diversity in their data teams. 

The US Department of Labor predicts 1.4 million computer specialist positions will be open by 2020. In the UK, an additional 182,000 jobs will be created by 2020. That's on top of the data and computer science jobs that already exist. An explosion of opportunity abounds for women and men alike. With organisations like Girls Who Code, the Women in Data Science (WiDS), Grace Hopper, and month's MIT Conference Talk Data to Me, there are plenty of opportunities to share stories, be inclusive, and grow the field to change the world.

Move 'Em Up, Not Out

It's become nearly cliché to suggest a woman leaves a job due to family obligations. It is rarely, if ever the case today. What doesn't work is the attrition rate, often not even realised and it begins much earlier in life.

According to Girls Who Code, 74% of middle school girls have an interest in STEM topics and careers, but that number drops exponentially to 0.4% by high school. That's quite a drop in potential candidates to the field long gone before they ever choose their college majors. But, the challenge of attainment and retention goes beyond education. 

Other obstacles abound once they're in the workplace such as feelings of isolation, a lack of mentorship or support, limited special assignments and not being looked to as equal players in the field. So, to combat this, many women simply take their knowledge and begin their own companies. They can source the data and communicate it to laypersons in an easy to understand manner so informed business decisions can be made to improve products or services. Baselines and benchmarks can be set and these women know it's important to question what they see, to run what-if scenarios, and to look at every angle.

Ultimately, the data science industry needs more women to bring their skills and perspectives to the table for better overall performance. Though women remain the minority in technology the goal is to raise awareness, to highlight opportunities and bring the benefits of diversity to light. With the abundance of programs, cross mentorship opportunities; women mentoring other women, but also mentorship from their male counterparts, and more educated companies on the benefits of a diverse data science team, women will continue to close the gender gap at a steady pace. 

Harnham are proud to have a client who is currently in search of female talent specifically. We specialise in junior and senior level recruitment in the digital and analytics field and pride ourselves on setting the bar for other firms to emulate. If you're interested in big data, marketing insights, and other roles within the data science fields, we've got a role for you. Check out our vacancies here or contact us for more information. 

Contact our UK Team at (020) 8408 6070 or email ukinfo@harnham.com to learn more.

Related blog & news

With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

Visit our Blogs & News portal or check out the related posts below.

Weekly News Digest - 11th-15th Jan 2021

This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of data and analytics. KDNuggets: 20 core Data Science concepts for beginners The field of Data Science is one that continuously evolves. For Data Scientists, this means constantly learning and perfecting new skills, keeping up to date with crucial trends and filling knowledge gaps.  However, there are a core set of concepts that all Data Scientists will need to understand throughout their career, especially at the start. From Data Wrangling to Data Imputation, Reinforcement Learning to Evaluation Metrics, KDNuggets outlines 20 of the key basics needed.  A great article if you’re just starting out and want to grasp the essentials or, if you’re a bit further up the ladder and would appreciate a quick refresh.  Read more here.  FinExtra: 15 DevOps trends to watch in 2021 As a direct response to the COVID-19 pandemic, there is no doubt that DevOps has come on leaps and bounds in the past year alone. FinExtra hears from a wide range of specialists within the sector, all of whom give their opinion on what 2021 holds for DevOps.  A few examples include: Nirav Chotai, Senior DevOps Engineer at Rakuten: “DataOps will definitely boom in 2021, and COVID might play a role in it. Due to COVID and WFH situation, consumption of digital content is skyrocket high which demands a new level of automation for self-scaling and self-healing systems to meet the growth and demand.” DevOps Architect at JFrog: “The "Sec'' part of DevSecOps will become more and more an integral part of the Software Development Lifecycle. A real security "shift left" approach will be the new norm.” CTO at International Technology Ventures: “Chaos Engineering will become an increasingly more important (and common) consideration in the DevOps planning discussions in more organizations.” Read the full article here.  Towards Data Science: 3 Simple Questions to Hone Python Skills for Beginners in 2021 Python is one of the most frequently used data languages within Data Science but for a new starter in the industry, it can be incredibly daunting. Leihua Yea, a PHD researcher at the University of California in Machine Learning and Data Science knows all too well how stressful can be to learn. He says: “Once, I struggled to figure out an easy level question on Leetcode and made no progress for hours!” In this piece for Towards Data Science, Yea gives junior Data Scientists three top pieces of advice to help master the basics of Python and level-up their skills. Find out what that advice is here.  ITWire: Enhancing customer experiences through better data management From the start of last year, businesses around the globe were pushed into a remote and digital way of working. This shift undoubtedly accelerated the use of the use of digital and data to keep their services as efficient and effective as possible.  Derak Cowan of Cohesity, the Information Technology company, talks with ITWire about the importance of the continued use of digital transformation and data post-pandemic, even after restrictions are relaxed and we move away from this overtly virtual world.  He says: “Business transformation is more than just a short-term tactic of buying software. If you want your business to thrive in the post-COVID age, it will need to place digital transformation at the heart of its business strategy and identify and overcome the roadblocks.” Read more about long-term digital transformation for your business here.  We've loved seeing all the news from Data and Analytics in the past week, it’s a market full of exciting and dynamic opportunities. To learn more about our work in this space, get in touch with us at info@harnham.com.

Seven Ways To Minimise Unconscious Bias In Your Recruitment Process

When it comes to the recruitment process, organisations will often take different approaches to securing their next hire. Yet, one challenge that remains the same across the board is the ubiquitous nature of unconscious bias. This typically means that individuals will favour those that look or think similarly to themselves. Not only is the potential for prejudice to arise an alarming issue here, but the impacts of unconscious bias can also have a detrimental effect on the hiring process, in both the short and long term. You could face missing out on a highly skilled and qualified candidate, as well as damaging opportunities for improving the diversity of the business. In order to address unconscious bias, organisations really need to take a moment to reflect and challenge their perceptions on the positive and the negative implications. Our own research demonstrates the opportunities of bolstering not only a diverse team in Data and Analytics, but an inclusive one too. Here are some core ways in which organisations can challenge and adapt their processes: Check your job descriptions It’s one of the simplest changes to make, but far too often overlooked. Many of us will use gender coded language without even realising it. It is therefore critical that all job descriptions are neutral, and that descriptive language is removed. Masculine-coded words such as ‘confident’ and ‘guru’ and feminine-coded words such as ‘understanding’ and ‘modest’ can really discourage individuals from applying for positions. Make use of panel-based interviews Over the past year, we’ve all become accustomed to a much more virtual way of working, which includes the recruitment process.  Our reliance on technology now plays an integral role in how we interview, test and hire candidates. When interviewing candidates, organisations should involve a range of different people (even if this is just in an observational role), as they may challenge your preconceptions and provide an alternative viewpoint. Instead of only involving the CEO and Managing Director, for example, make sure you have individuals from other departments and areas within the team sitting in too. Interviews should instead focus on skills-based tasks  In order to minimise the unconscious bias that permeates the recruitment process across industries, interviews need to focus on skills-based tasks. Importantly, hiring managers should be assessing the suitability for a role, so practical, skills-focused tasks are important in establishing this. Appoint an external inclusion agency If you’re stuck for where to start when it comes to improving the ways in which you plan and execute your hiring strategies, it could be worthwhile to seek support from an external agency or individual that specialises in inclusion. Their insights, experiences and knowledge will be able to support an organisation to ensure that their hiring process minimises the impacts of unconscious bias. Facilitating discussions and training In the same way that liaising with external experts can support an organisation, so to can introducing training sessions. Stamping out unconscious bias requires us all to challenge our ways of thinking to create an inclusive culture for all. Regardless of whether this is during the recruitment process, through onboarding or once an individual is working within the business, facilitating discussions and training can help. It should be noted though, that generalised training to minimise unconscious bias training isn’t always effective, so this should be assessed and planned according to relevant objectives and goals. Advertise roles through different channels To ensure that you are reaching a diverse pool of talent, hiring managers should ensure that positions are advertised across a range of different platforms. It may be the case that highly skilled professionals from different backgrounds do not all source new positions through the same websites or streams. Improving this access will ensure that you are not selecting candidates from the same pool of talent.  Set specific diversity and inclusion goals It’s crucial to remember that taking steps to minimise and remove these biases is just one part of a much bigger challenge that organisations are facing in order to action change. Firms need to assess their long-term diversity and inclusion goals in order to ensure that removing biases is part of an embedded strategy. Internal strategies must be reviewed and assessed in order to ensure that the approach to the recruitment process provides equal and fair access and opportunities for all to thrive. In the Data and Analytics sector, it’s key for leaders to take action to mandate some core strategies to engage and include a diverse team of talent. If you're looking to make your next hire, or are searching role yourself, get in touch with our expert consultants or take a look at our latest Data & Analytics jobs here. 

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