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Matt Conflitti, Transforming Data Into Insights

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Software companies produce a lot of data. In fact, most American businesses produce data constantly. But what do they do with that data? Well, most don’t do anything at all. That’s too bad, because data can do a lot for the businesses that know how to use it. 

That’s where data science comes in. Data science is all about gathering and using knowledge. Data scientists mine data, gather insights from that data, and then apply those insights to create growth and efficiency. 

To get some more insight into data science, we talked to Matt Conflitti, who works as a data scientist here at eoStar. 

How It Started 

eoStar didn’t always have a data science team. Matt started working for eoStar just over two years ago. 

Like a lot of other data scientists, Matt took a winding road to get into the field. That’s because data science encompasses a lot of knowledge. Matt noted that although data science has gained some more clear-cut definitions recently, it still contains overlapping skill sets. For example, “data science and machine learning engineering are kind of interchangeable today,” Matt explained. 

Matt started with a degree in Computer Science and Math from Grand Valley State University. After various software development jobs, he started working for the accounting firm KPMG. There, several of his projects involved machine learning and data science. He loved those projects and wished he could pursue more of them. 

Fortunately, Matt got a LinkedIn message inviting him to do just that at eoStar. Matt accepted, becoming the first member of eoStar’s data science team. 

Matt’s Work with Data Science 

At eoStar, Matt is laying the groundwork for a full data science platform. He’s working on a few different initiatives, including: 

  • Recommender systems — determining which products work best for our clients’ customers. 
  • Forecasting and demand planning — finding the best models for warehouse forecasting and inventory management. 
  • Clustering — creating rules by examining and applying different data characteristics. 

“I don’t want to be cliche and say I like them all,” said Matt when we asked about his favorite project, “but [because] I’m someone who loves the details of things…all of the projects have been great.” 

The Goal 

Data is valuable, Matt noted, but only if it gets used properly to produce usable insights. Again, not everyone uses their available data. 

At eoStar, we want to do things differently. Thanks to Matt and his team members, we do use our data, and we use it to make our clients’ lives easier. Matt’s work helps businesses transform their workflows in a positive way. This way, our clients can gain efficiency and higher customer satisfaction rates. 

Learn More about eoStar’s Work with Data 

Thanks to eoStar’s data science efforts, we can offer services that our competition cannot. Get in touch with us now to learn more about those services. We’d love to answer your questions about how our work can help you keep your business in its best shape. 

Route Accounting Solutions

So, What Exactly is a Data Scientist?

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What is a data scientist?

During our 2020 virtual user conference, one of our sessions went through  eoStar Analytics. During the session our very own data scientist talked about the future of data, analytics, and how to use information to make more informed decisions for your business. But there was one question on a lot of people’s minds, what is a data scientist?

The job is to the fulfill the formula of Problems + Data => Models + Insights. They are able to map expert knowledge and context into real-life solutions. An unofficial definition of a data scientist has become: someone who knows more about math and statistics than a computer scientist and more about computer science than a mathematician or statistician.

“A Data Scientist is a professional who extensively works with Big Data in order to derive valuable business insights from it. Over the course of a day, the Data Scientist (DS) has to assume many roles: a mathematician, an analyst, a computer scientist, and a trend spotter.” – IntelliPaat[1]

Data Science is a rapidly changing field, so anyone that takes on the role of data science needs to be able to keep up with the latest research and techniques. Due to the cloudiness of what exactly a data scientist is and does, there is an increasing overlap between data science and machine learning. Machine learning includes things like computer vision, speech recognition, neural networks, etc. The person that implements the models and insights data scientists come up with is traditionally called a Machine Learning Engineer (MLE), but this can be interchangeable with “Data Scientist” at a lot of organizations.

A typical workflow for a data scientist or machine learning engineer is as follows:

  1. Scoping
    1. Working closely with the product team, the DS will gather the requirements around a particular business problem and determine if a solution is possible given the available data.
  2. Research
    1. This process involves gathering the necessary datasets, cleaning them, and experimentation on the data. This is the phase where the DS really gets to understand the relationships within the data as well as outside of the data. Research also goes into figuring out which approach will be best to solve the problem.
  3. Modeling
    1. Once a few approaches are selected to explore, the DS fits the various models to the data and benchmarks are calculated to determine which system will work best in a real-life scenario. The goal of this phase is to converge on a single approach to deploy.
  4. Deployment
    1. Finally, the model or system is deployed and put into production so that it can be integrated into the existing software ecosystem.

As the beverage industry continues to evolve with new SKU’s, expanded product offerings, and tightening inventory, data and analytics are becoming more essential than before. At eoStar we are fortunate to have a team focused on turning your data into insights and helping you turn those insights into action. To learn more about how our products are using data and analytics to improve your business, talk to one of our sales experts.


[1] https://intellipaat.com/blog/what-is-a-data-scientist/