Qualities of a prized Data Analyst or Data Scientist
How does a Data Analyst or a Data Scientist in a business facing role create impact? Would your answer be — expertise in statistics, SQL, machine learning and other esoteric data skills? In my experience, these skills are only a small part of what determines the success of someone in a data partner role. Read on to find out what it takes to be a much sought-after data professional.
In most organizations, data teams play an outward facing role. Members spend a significant portion of their time working with business and product — understanding their requirements, their short and long term goals and making recommendations to refine their roadmaps and strategies.
In a complex role like this, technical skills alone don’t quite cut it…
In broad strokes, I’d categorize these “other” skills into
- Building trust
- Customer focus
- Skillful communication
What do each of them look like in practice?
Building Trust
“In God we trust, All others must bring data”. What happens when this somebody who brings data is a data specialist themselves? Then they must bring “trust”.
Building trust rarely happens overnight but there are some ways to accelerate it. Stakeholders trust data partners who keep multiple perspectives in mind when making a recommendation. They seek people who are curious and proactively surface insights for better decision making.
A self-managed analyst or a scientist, who can work closely with people in different functions such as product, user research, marketing will be able to create a balanced viewpoint. This in turn will fuel critical recommendations. It is a great way for an analyst to understand a problem beyond its description and build a product, user and business perspective.
Having a Customer Focus
How does this skill manifest? Data Analysts and Scientists admired for their focus on customer needs have a demonstrated ability to see and frame the bigger business questions.
They step into the shoes of the stakeholder when conducting an analysis which allows them to think ahead. This approach of viewing a request from the stakeholder’s perspective opens up opportunities to go beyond their mandate (of “providing insights and recommendations”) — setting up a virtuous cycle of value creation for the stakeholders.
Skillful Communication
You have heard it before — Data Scientists are great communicators. What does this mean in a real world business setup?
Highlighting salient features of an approach, its limitations, explaining nuances in the results, cautioning on how the results should not be interpreted and finally, distilling insights into key takeaways and communicating conclusions — these, are a few things to keep in mind when honing this skill.
The other critical part of good communication is asking probing questions that promote dialogue and discussion.
In conclusion…
Data partners bring the much needed data perspective to the table.
Use these techniques described to ensure your qualified opinions are trusted and your recommendations translate into business decisions.
