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Valkyrie Scientist Spotlight: Matt Paff

The Valkyrie team is made up of a group of engaged, data-driven scientists, who specialize in various areas of science, artificial intelligence, and machine learning. This month, Valkyrie is highlighting Data Scientist Matt Paff in our Scientist Spotlight blog.


Prior to joining the Valkyrie team, Matt successfully completed his PhD in cell and molecular biology and then broke into the field of data science. During his time in grad school, Matt was primarily focused on “wet lab” empirical research, doing biological experiments and collecting data from the bench-top. He eventually developed an interest in the capabilities of computational biology and how it’s used in the field of data science. From there, he shifted his focus to designing projects that allowed him to combine the use of empirical methods with computational and bioinformatic methods, using gene expression analysis and modeling approaches. He said, “while I loved pure research and biology, I wanted to apply those skills in a more applied way, and data science offered me that opportunity to leverage complex datasets and apply them in a way that allows for immediate and significant impact.”


Joining Valkyrie in 2019, Matt has continually developed and grown in the field of data science. He expressed how data science has opened up a wide variety of opportunities in the industry for him. Getting into analytics and data science earlier in his research allowed him to continue to do what he loved in a way that was also more applicable to real life. Not only has being a data scientist helped him to understand the importance of data and how and why it is collected, but it has also illuminated the importance of being able to effectively communicate that data to individuals or groups that may have less experience with data science.


While data science has become his ideal career, Matt also shared with us a few ways in which he hopes the industry will grow, such as additional inclusion of data scientists in non-data aspects. He said, “I would like to see greater integration of data scientists within the product life cycle, in terms of collaboration with other stakeholders on a project.” He has seen several situations in which organizations isolated their data science and analytics teams. Working in such a manner keeps the data scientists far removed from the product development cycle so that it is a struggle to deliver an impactful solution that fits within the product vision. Matt believes that making an effort to include data scientists in other non-data aspects of the product would create more seamlessly integrated data products and non-data science stakeholders with a better understanding of what can and cannot be accomplished with data science. Ultimately, Matt believes this integration and knowledge share will create truly data-driven organizations.


Having started from a background in empirical research, with little emphasis on computational informatics, Matt was able to successfully redirect his career and shift his focus towards a new passion, the field of data science.