Three attributes of a good data scientistPosted on July 24, 2015 by TheStorageChap in Big Data and Analytics, Data Scientist
Big data has rocked the business world with the promise of uncovering critical insights and gems of information that have the power to transform strategy and operations for the better, and drive innovation. But, to do this you need curious and inquiring minds to analyse and extract meaning from it – the data scientists. So what are the three attributes of a good data scientist?
Armed with a wide range of expertise including computer science, modeling, statistics, analytics and math along with strong business acumen, data scientists have the complicated task of not only exploring data in creative ways, but communicating the findings of their investigations to both business and IT leaders in a persuasive and authoritative way. Good data scientists have a sixth sense for scouting out the most pertinent issues to address and find solutions that could have a tremendous impact on the organisation.
With this responsibility, these experts hold immense power over the future of the business. What are the qualities you need when you look for a good data scientist? Here are a few key behavioural and attitudinal traits:
- Focusing on the future – Due to the nature of their work, data scientists will look through the crystal ball to predict the future landscape rather than reflecting too much on present or past performance. For example, monitoring for and anticipating new, emerging technologies that can collect ever more data (such as wearables or distributed sensors, like smart meters or weather stations) and are likely to impact the business will be key for these experts. It’s then about identifying the ways in which the organisation can use this data – conveying this back to the wider business, whilst working with IT to ensure the right levels of data security and protection of the data under analysis.
- Providing multiple, creative solutions to anticipated problems –Data scientists are all about predicting and solving future problems and scenarios through exploring data and discovering multiple disparate creative ways to address a challenge. There might be a dozen different things that cause an issue with, for example, customer demand for a product; some of which might be how consumers have felt about the marketing (social media insights mining) and others might relate to the product stock location in stores (surveillance video analytics) and others still might relate to the product itself.
- Thinking outside the box – With a talent for looking at and interrogating data in different ways, they will explore both the internal and external environment. Whether it’s monitoring consumer trends and behavioural data or looking through internal organisational data to see how it might impact the business, their unique skill is interpreting all this data and delivering real insight and recommendations to the business.
Tasked with shining light on dark, hidden insights, data scientists can draw on their expertise to drive competitive advantage and address pressing business problems. With a focus on exploration and discovery, their day job is very different to traditional business analysts. However, they should strive to complement the team and work together to create a well-oiled operation. This collaboration will help drive transformation and innovation across the business, which is more important than ever before.