Rianne van der Loo (ADC) on her career and diversity in data science

Rianne van der Loo has been active in the consulting and technology industry for over twelve years. After spells with Deloitte, Boston Consulting Group and Google, she earlier this year joined Amsterdam Data Collective (ADC) as its Chief Commercial Officer. An example for many women in the world of data science, we sat down with Rianne to discuss her path to her current role and diversity & inclusion.

After a decade at Google, you made the switch to Amsterdam Data Collective. What motivated you move?

Throughout my career three elements have been a red thread: people & culture, customers and data. I studied Econometrics, but chose to broaden my horizon as a strategy consultant at Boston Consulting Group.

Keen to build and develop more longer-term relationships, I joined Google. There I also was able to developed my commercial and operational skills across different roles.

After ten years, I felt it was time for something new. I was looking for a place where I could combine my background and experience with a challenge to help teams grow in a fast paced environment. I found this at Amsterdam Data Collective: making an impact with data, helping customers to become more successful and working with an amazing group of people.

Where do you find daily positivity and motivation at Amsterdam Data Collective?

It is a bit of a cliché, but it is the people I work with that bring me the most happiness in my job. Ultimately, I spend a lot of time at work, so I want that time to be enjoyable in a positive environment with people I can learn from and share a laugh with. For me, it is important that work and life are not two completely separate things. I like to work with people that I also enjoy spending time with; that is what makes it nice to come into the office every morning. 

Apart from that, I’m passionate about the core business of Amsterdam Data Collective – helping organisations apply data science to create a positive impact for business and society.

And I like to work in a fast-paced environment where people have a “can-do” mentality. This is a central part of the Amsterdam Data Collective culture – we see an opportunity and try to grab it; we see the results and measure them; and we adapt where needed. I enjoy being part of a growing collective at Amsterdam Data Collective where people share my ambitions and growth mindset.

Data science still is a male-dominated world. Hoes does Amsterdam Data Collective foster diversity & inclusion and inclusive leadership?

Diversity and inclusion are things that Amsterdam Data Collective has always focused on implicitly, but as we continue to grow, we want to focus on them more explicitly by being conscious of balanced hiring. A diverse group of people consistently produces better results. We strive to create a diverse team in terms of gender, age, ethnicity, and the other unlimited factors that define diversity.

When specifically considering gender, it is also important to consider masculine and feminine characteristics, which we have closely looked at within the Management Team. We try to discover our personal leadership attributes, what we can learn from each other, and where we have any blind spots to ensure we have a balanced team. Working with people who do not always share my perspective challenges me to think creatively and perform in new ways, leading to better solutions and overall results.

In addition, we like to promote from within and give our future leaders the resources they need to succeed. There are endless opportunities to take initiative within projects, as well as training sessions to develop both hard and soft skills. We offer a lot of freedom, which empowers people to take ownership. For me, ownership is a foundational quality of successful leadership.

Specifically on leadership inclusiveness, what are in your opinion the most significant barriers to creating a diverse leadership team?

In general, when people talk about leadership attributes, it is the masculine traits that are highlighted first. These traits include competitiveness, strength, risk-taking, and assertiveness, compared to the typically feminine leadership traits that include collaboration, empathy, intuition, and attention to detail. The latter are still considered “nice to haves” but not requirements when hiring for leadership positions.

As long as companies continue to judge their leaders on a rigid set of characteristics, they miss the opportunity to hire people who bring a fresh perspective to their organisations.

In addition, many large companies still hire from within an “old boys” network that does not foster inclusive leadership. Hopefully this is something that will continue to change over time, but for now there is still a common theme of current leaders looking for people who reflect themselves. Instead, companies should take more chances in terms of not only looking at what a candidate has already done, but also what a candidate can bring to the table.

Reflecting on your own career, how important is it to have a mentor to grow as a leader?

Throughout my career I have had several mentors, some of whom were also my managers, and some of whom were colleagues who I explicitly asked to mentor me. These relationships hugely impacted my career, especially since I tend to always be in action mode without leaving a lot of time for reflection. Scheduling conversations with my mentors forced me to make conscious plans about what I wanted to learn and how I wanted to develop within my career.

Sparring with others provides a valuable opportunity to hear how people with different perspectives would approach a situation, and then reflect on it from your own point of view. A mentor can also help provide direction on what skills you want to develop and how you can experiment with that; however, it is ultimately up to the individual to translate such learnings into actions.

Finally, for those considering a career in data science, what advice would you give?

To start off, you must be willing to embrace change; you should enjoy things getting turned upside down. It is an industry for people who like to see the possibilities, are open to growth, and want to take initiative. However, it also demands a lot of resilience and independence: figure out your own path by seeking out opportunities rather than waiting for them to come to you.

Additionally, it is not a requirement to excel in technical skills to find your place in the technology and data science industry. Even though there are many opportunities for data scientists, software developers, and data engineers, there are other roles present, including in sales, marketing, and product management. Find out where you can contribute.