8 Reasons to Build Communities in Data Science

The number of data science communities is continually on the rise both online and in-person. From evermore Meetup groups to Slack workspaces and other community platforms out there, people and organizations involved with data science, machine learning and Ai are finding opportunities to connect with other professionals and organizations whether they are scientists, engineers, developers, service providers or new entrants.

These communities exist for different purposes including learning and knowledge sharing, expert networks and advisory groups, membership communities, hyper local events, and more. There are also brand communities created by companies to promote their brands, which provide a hub for their users to come together and engage with each other.

If you are an entrepreneur or notable leader in your company and wondering how your organization can benefit by getting actively involved in data science communities, this article is for you. It explores why organizations like yours are investing their time, efforts, and resources into community building and points out how you can benefit by creating a community or joining existing ones.

  1. Bringing like minds together

Data science can be lonely, especially these days where many data scientists work remotely. Professionals who are not connected to a community may easily find themselves being isolated and bored. They may also experience frequent burnouts which reduce their productivity. But the practice of data science does not have to take anyone into perpetual boredom. Things can get a little more social and interesting by facilitating a hub to bring like-minded people together to interact and solve problems.

  1. Knowledge sharing hub

Being a vast field, there is a need more than ever to create communities in data science where there can be a free flow of knowledge, ideas, and information sharing. Experts, beginners, and organizations will benefit if there is a place they can ask questions and receive quality feedback.

Q&A sessions in communities provide the opportunity for members to find out more about certain topics. A single question asked can break the ice and open up a floodgate of discussions that will unlock a massive exchange of innovative thoughts and ideas.

  1. Exchange of best practices

Data science as a field is evolving quickly thanks to the knowledge being shared widely in the industry. You can take this further and drive innovation by facilitating the exchange of best practices and research. This can be achieved by creating special events and forums where there will be keynotes, panel discussions, open salons, and breakouts to discuss current and future industry trends.

  1. Opportunities for co-creation and collaboration

The free flow of information in communities will soon lead to some form of pairing as  professionals of like minds discover themselves. This will evolve into collaboration and co-creation efforts that can birth new innovative ideas, products, and solutions.

  1. Get product feedback and ideas for innovations

Create a community of product users where you can follow up with customers, ask direct questions and gather feedback that will help your ideation process when improving your products or creating new ones, based on your understanding of customers’ pain points.

  1. Engage with your community

Brand communities are only active when brand owners constantly engage with members. You need to know what your people talk about, what they are interested in, and what they need. Building robust relationships with your community will result in mutually beneficial interactions. You will get information on what your customers truly require as well as their challenges. This will help you explore and create new and exciting ideas that represent your customers’ needs.

  1. Opportunity to fight bias

Unfortunately, there is usually a general bias in tech. It could be gender or racial bias or other types of biases. For example, tech communities are still predominantly dominated by men, and women are often faced with gender hurdles that keep them from advancing in their careers.

A study released last year by Accenture and Girls Who Code reveals that 50% of women dump tech careers at 35 and more women are leaving tech roles at an almost 50% higher rate than men. This trend shows that without strong communities supporting women in data science, many more women might soon become part of the stats. However, the creation of female-forward communities, such as DSS Elevate helps to close the gender gap in tech.

  1. Become a reliable partner

Creating and building data science communities helps build trust with your audience. You can grow your community by continually engaging it, answering important questions, and allowing the free flow of information between members. An active and healthy community will continue to grow and attract more people. With time, you will not only gain recognition for your work as a data scientist or solution provider, but you will also become a trusted and reliable partner for all things data science.

Conclusion

Like other professional communities, data science communities exist to improve the skills and knowledge of members regardless of their expertise level or sub-areas. Communities encourage professional dialogue, ideas exchange, collaboration, innovation, and co-creation. For organizations, building communities will bring you closer to users. You will get helpful feedback on your products as well as ideas for developing new products and solutions that users mostly require.

You can create or leverage data science communities for business and organizational growth, for effective product delivery and utilization, and to nurture your services within your user base.

However, it is important to note that communities exist for mutual benefits. Your focus should not be based on what your organization stands to gain alone but to create an interesting and impactful platform for all members.