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4 Things a Data Scientist Can Do for Entrepreneurs Virtually every type of company can benefit from a skilled data scientist.

By Michael Li Edited by Dan Bova

Opinions expressed by Entrepreneur contributors are their own.

These days, there is no shortage of data -- even the earliest stage entrepreneurs are finding themselves sitting on mounds and mounds of it -- and it often leads to the same question: How can I use this to help me grow?

At The Data Incubator, we train over 100 data scientists to enter industry every year. The fellows have joined with some of the largest corporations in America, including Capital One, AIG and eBay, as well as budding startups such as Betterment and YouNow. They have joined larger veteran teams, and have been brought on to build data and analytics at their companies.

Related: Hire Better Talent With a Big-Data Scientist

Virtually every type of company can benefit from a skilled data scientist. Here are four major things they should be doing:

1. Growth hacking

Legendary investor Paul Graham is credited with saying "startup equals growth" and it's a lesson every entrepreneur knows well. But startups are often strapped for cash. Having a data scientist focused on growth hacking can take advantage of the huge amounts of social data and web-analytics to implement low-cost, high-impact marketing campaigns that make the most of each marketing dollar.

2. Customer retention

Bain & Company found that just a 5 percent increase in customer retention can increase profits by 125 percent. Because of this, companies are hiring data scientists to increase revenue, extend lifetime value and reduce user churn. Advanced data scientists can analyze customer behavior and target communication to not only keep customers engaged, but to encourage more engagement, and by extension, more purchasing. Skilled data scientists can even identify brand advocates who will evangelize your company to new users.

Related: Big Data Is No Longer Confined to the Big Business Playbook

3. Personalizing products and services

What do your customers really want? Do women really want theirs in pink? What is gen-Y looking for? Chances are, this is hidden inside your sales, marketing and web data. Hiring a data scientist to comb through this can help companies decide to build the products and services their customers really want and differentiate themselves from the competition.

4. Marketing optimization

How are your ad dollars being spent? Are they targeted to your core customers or being dumped into a click farm? Are those ads resulting in actual conversions and purchases? Who is most likely to click? While you may not have the resources for a full-service marketing strategy yet, there is significantly more you can do with your resources than reorganizing your ads based on their cost per click. A trained data scientist can optimize for all these questions and more.

Hiring a data scientist as an entrepreneur is one of the most sound investments you can make in your company. We have covered just four of the most popular ways that they can deliver huge returns. If you are interested in learning more about what the data scientists we have trained are doing, take a look at our blog, where we highlight some of our alumni now working in industry with partners such as The New York Times or Betterment.

This article was written by a member of the AlleyNYC contributor network. AlleyNYC is one of the world's largest innovation hubs, helping foster the growth of startups in its flagship location in New York City. Entrepreneur Media is a partner and investor in AlleyNYC. If you would like to learn more about AlleyNYC and how to apply for membership visit here.

Related: Why Businesses Fail: A Data Expert Explains It All

Michael Li

Entrepreneur and Founder, Data Scientist

Michael Li has worked as a data scientist (Foursquare), quant (D.E. Shaw, J.P. Morgan), and a rocket scientist (NASA). He did his PhD at Princeton as a Hertz fellow and read Part III Maths at Cambridge as a Marshall scholar.

At Foursquare, Li discovered that his favorite part of the job was teaching and mentoring smart people about data science. He decided to build a startup that lets him focus on what he really loves.

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