Most Important Skills For A Senior Data Scientist At Newfront Insurance
According to Matthew, a Senior Data Scientist at Newfront Insurance, crucial skills involve translating stakeholders' ideas and concerns into technical projects and solutions, which requires "understanding requests" and being a "great communicator." Matthew also emphasizes the importance of SQL and Python for success in data science roles, skills that Matthew learned on the job and considers vital for anyone pursuing a data science career.
Stakeholder Communication, Technical Translation, SQL, Python, Business Understanding
Advizer Information
Name
Job Title
Company
Undergrad
Grad Programs
Majors
Industries
Job Functions
Traits
Matthew Slodowitz
Senior Data Scientist
Newfront Insurance
University of Michigan
Mathematics, Data Science, Statistics
Insurance, Technology
Data and Analytics
Greek Life Member
Video Highlights
1. Translating stakeholder needs into technical solutions is crucial for data scientists. This involves understanding business requirements, expectations for visualizations, and how to convert these into actionable technical projects.
2. Strong communication and stakeholder management skills are essential for collaborating effectively with data engineers, software engineers, and business stakeholders on data science projects.
3. Proficiency in SQL and Python are highly valuable skills for data science roles. SQL is fundamental, and Python is increasingly important in the data science community.
Transcript
What skills are most important for a job like yours?
That's a good question. Some of the skills I think are really important when you're working as a data scientist are knowing how to decipher a stakeholder's ideas and concerns into a technical project and a technical solution. This is something I've encountered often in my career.
Whether you're a data scientist, or working with data engineers or software engineers, you have to be able to translate stakeholder requests and problems into a technical solution. This includes understanding what business solutions look like and what expectations you have for visualizations.
You really need to understand what the stakeholder wants and then translate that into a real technical solution that can be integrated into a mainstream business solution. It's about understanding requests, working with stakeholders, and being a great communicator when it comes to projects.
One big skill I learned on the job, and think is super important for anyone in a data science role, is understanding SQL. SQL is a big thing. As we move forward in the data science community, Python is also a big thing to learn.