November 6th, 2018
Data Science Careers in Supply Chain
The explosion of big data around the world is proof that data and analytics are bringing all sorts of value to businesses. This is true for the supply chain and logistics industry, as well. More than ever, organizations need competent data scientists to help them make sense of the data collected.
What is Data Science and What Does a Data Scientist Do?
Academic research suggests that the current state and future potential of data science, analytics, and big data in supply chain management (SCM) demands training next-generation data scientists on the use of predictive analytics in SCM. This explains the need for more data scientists in the supply chain industry.
Are you the Data Scientist that Supply Chains Need? via @ajilon: http://ajilon.co/1UhnnxN #datascience #bigdata #supplychain #logistics
Supply chains rely on data scientists who can capitalize on the data. For data scientists, supply chains represent an attractive industry to grow and apply their expertise. However, what does it take to become competitive as a professional data scientist?
What kind of skills are supply chains looking for in a data scientist?
In the recent O’Reilly report and eBook What It Takes to Succeed as a Professional Data Scientist, Jerry Overton, a Data Scientist and Distinguished Engineer at CSC where he is head of advanced analytics research and founder of CSC’s advanced analytics lab, outlines best practices for current and aspiring data scientists for making good decisions through what he calls “data science that works.”
Data science that works
“Data science that works” is a set of consistently useful data science practices. They extract simple heuristics for making good decisions. In a nutshell:
- It’s important to value the right set of data science skills
- It’s critical to find practical methods of induction where to refer general principles from observation and then reason about the credibility of those principles
As Overton notes, a data scientist has to be able to take a guess at a hypothesis and then use it to explain the data.
How to be an Agile Data Scientist to Better Help the Supply Chain
According to Overton, an agile data scientist works in small iterations, pivots based on results, and learns along the way. “Agile data science lets you deliver results on a regular basis and it keeps stakeholders engaged.”
Data scientist’s skill set: A pragmatic approach
There is currently a shortage of data scientists with a combination of subject matter expertise, mathematics, and computer science. However, according to Overton, the skill set you need to be effective tends to be more specific and much more attainable than mastering the details of machine learning algorithms, as shown in the graph below:
A more pragmatic view of the required data science skills. Credit: Jerry Overton
For Overton, the most important quality to look for in a data scientist is the ability to find useful evidence and interpret its significance. This changes the view of both what to look for from data science and what to look for in a data scientist. It is more important for a data scientist to be skilled at engaging SMEs in agile experimentation.
Hypotheses and the Data Scientist
A background in mathematics and statistics is necessary to understand the details of machine learning algorithms. To be effective at applying learning algorithms requires a more specific understanding of how to evaluate hypotheses, according to Overton.
“We tend to judge scientists by how much they’ve stored in their heads.” says Overtone in the report. “We look for detailed knowledge of machine learning algorithms, a history of experiences in a particular domain, and an all-around understanding of computers.” However, he believes it’s better to judge the skills of a data scientist based on their track record of shepherding ideas through funnels of evidence and arriving at insights that are useful in the real world.
Check out our white paper to Learn How the Internet of Things Affects the Supply Chain.
Susan Fourtané is a Science & Technology Journalist with vast experience writing and reporting on big data analytics, and supply chain & logistics for industry publications. Susan frequently attends supply chain & logistics events in Europe, being at the heart of new research, and innovation. You can follow her on Twitter @SusanFourtane