In 2012, Harvard Magazine proclaimed that data scientist is the sexiest job of the century. Granted, the people making this claim consisted of a senior advisor to Deloitte Analytics and a data scientist from Greylock Partners, but they made a valid argument. Referencing Jonathan Goldman's work as an example, the People You May Know feature on LinkedIn grew from an experiment on how technology can make predictions and recommendations for us based off our behaviours and preferences. This wouldn't have been possible without data scientists.
Data scientists are good for businessEvery business is increasingly interested in mining data and analytics to learn more about their customers in order to yield higher returns. Companies are often in competition with one another to figure out how they can collect more data and do it more efficiently than anyone else. Data scientists specialize in determining what data is important to collect. "Once [a business has] data," says Greylock VP of Talent, Dan Portillo, "they really need people who can manage it and find insights in it."
Biggest challenges for data collection and analysis
Our development team will tell you that data collection is complex, but entirely doable. Interpreting this data is where the hard part comes in. Data needs to be collected comprehensively to include as many insights as possible, but the more you collect, the more complex the analysis becomes. Analytics need to be filtered and categorized properly to make the information digestable. Figuring out what you need to show and innovating in the analytics reporting field can also be difficult, especially when services like Google Analytics are so ubiquitous and well-known.
Elize Shirdel, data scientist and CEO and Founder of Date Night, says "One of the key issues with communicating data analytics insights is providing too much information. Top-level managers may not have the time to weed through tiny seedlings. They are looking for the low-hanging fruit - a few key insights that they can act upon to elicit true value."
How to communicate value of data to CEOs and marketing managers
Shirdel has a few tips for communicating the right information to key stakeholders:
1. Don't present too much data.
2. Don't go into too much detail - managers don't care about how you drew thresholds.
3. Know your audience - some managers would welcome the opportunity to mull over charts and figures with you to glean insights... some would not. Some just want five bullet points with the conclusions.
4. Be patient. Where data scientists fit into the corporate pyramid is a complicated issue. You are gleaning insights from the very core of the business.
These questions are valuable to answer during conversations with executives and key stakeholders, but are also important to consider when developing an analytics platform or feature.
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