What Makes a Well-Rounded Data Science Team?
We’re continuing our look into what roles you need to fill to create a perfect data science team by explaining the roles filled by the Machine Learning Scientist; Data Engineer; and Engagement Leader.
Creating a data science team requires painstaking precision. It should be multifaceted. Not only should it consist of data scientists, with different specializations and disciplines, but it also requires a strong support system to round it out.
So, who will you have access to on any engagement with Pandata? First, let’s start with a quick review of two positions we discussed in a previous post: The Data Scientist and Analyst.
Data Scientist, aka the “Data Wizard”
A keen problem solver who can frame complex problems, apply advanced statistical techniques to raw data to derive insight and meaning, and communicate key insights to leadership. Skills include: distributed computing, predictive modeling, leadership and interpersonal communication, storytelling and visualizing, math, statistics, and machine learning.
Data Analyst, aka the “Data Detective”
Cleans, massages & organizes data to perform statistical data analysis and provide critical reports. Skills include: spreadsheet tools, database systems, communications and visualizations, math and statistics.
The rest of the team
But it takes more than two people to tango on a data science team. Let’s meet the other members of your company’s data division: the Machine Learning Scientist; Data Engineer; and Engagement Leader.
Machine Learning Scientist, aka the “Data Whisperer”
A specialized data scientist who leverages advanced algorithms and study design to develop next-level predictive models and extract value from complex data. Skills include: distributed computing; data mining; predictive modeling; algorithm development; big data modeling; advanced mathematics; and statistics.
Data Engineer, aka the “Data Pipeline Builder”
Develops, constructs, tests and maintains architectures. Skills include: distributed computing; large-scale database systems; data modeling; data APIs; and data warehousing solutions.
Engagement Leader, aka the “Data Science Team Leader”
Maintains the customer engagement and experience. The liaison between the customer and the technical team. Skills include: project and traffic management; customer service; interpersonal communication; problem-solving, reporting and contracting; as well as database systems; data mining; and predictive modeling.
To learn more about how the well-rounded team at Pandata can help address your data pain points, drop us a line.
Nicole Ponstingle is the Chief Strategy Officer and a Partner at Pandata.